Exercise guidance device, exercise guidance method and storage medium

Abstract

An exercise guidance device includes a memory that stores a program and at least one processor that executes the program. The processor obtains a guidance content pertaining to a predetermined form indicator from among guidance contents about a movement of a body of a user in exercise. The processor obtains a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise. The processor provides the obtained guidance content to the user who is doing the exercise, by performing, with respect to each guidance timing during the exercise, a series of processes of providing a first guidance content corresponding to the each guidance timing and providing a second guidance content corresponding to a result of the form indicator value that the processor obtains while providing the first guidance content, in order named.

Description

REFERENCE TO RELATED APPLICATIONS

[0001] This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 2024-161073, filed on Sep. 18, 2024, the entire contents, including the description, claims, abstract and drawings, of which are incorporated herein by reference.TECHNICAL FIELD

[0002] The present disclosure relates to an exercise guidance device, an exercise guidance method and a storage medium.DESCRIPTION OF RELATED ART

[0003] There is disclosed, for example, in JP H2-203842 A a conventional running determination device that detects acceleration of movement of the body of a user in the up-down direction and acceleration of movement of the body of the user in the front-back direction and determines whether his / her running form is good.SUMMARY OF THE INVENTION

[0004] According to an aspect of the present disclosure, there is provided an exercise guidance device including:

[0005] a memory that stores a program; and

[0006] at least one processor that executes the program,

[0007] wherein the processor

[0008] obtains a guidance content pertaining to a predetermined form indicator from among guidance contents about a movement of a body of a user in exercise,

[0009] obtains a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise, and

[0010] provides the obtained guidance content to the user who is doing the exercise, by performing, with respect to each guidance timing of guidance timings during the exercise, a series of processes of providing a first guidance content corresponding to the each guidance timing and providing a second guidance content corresponding to a result of the form indicator value that the processor obtains while providing the first guidance content, in order named.BRIEF DESCRIPTION OF DRAWINGS

[0011] FIG. 1 is a block diagram showing an exercise guidance system according to an embodiment(s) of the present disclosure.

[0012] FIG. 2 is a block diagram m showing a functional configuration of a motion sensor device.

[0013] FIG. 3 is a block diagram showing a functional configuration of a smartphone.

[0014] FIG. 4 shows examples of contents of a guidance content database.

[0015] FIG. 5 shows examples of contents of the guidance content database.

[0016] FIG. 6 is a block diagram showing a functional configuration of a wireless earphone(s).

[0017] FIG. 7 is a flowchart showing a control procedure for a running form guidance process.

[0018] FIG. 8 shows an example of a lesson selection screen.

[0019] FIG. 9 is a flowchart showing a control procedure for a knowledge level determination process.

[0020] FIG. 10 is a flowchart showing a control procedure for a condition level determination process.

[0021] FIG. 11 is a flowchart showing a control procedure for a guidance content provision process.

[0022] FIG. 12 shows the structure of a lesson that a user can take in a running form guidance mode.

[0023] FIG. 13 shows examples of voice contents of Lesson 2 to Learn Basics of “Landing Impact”_Hard.

[0024] FIG. 14 shows examples of voice contents of Lesson 2 Focusing on “Landing Impact” Drill Easy.

[0025] FIG. 15 is a flowchart showing a control procedure for the running form guidance process according to a modification.

[0026] FIG. 16 is a flowchart showing a control procedure for an improvement-required form indicator determination process.

[0027] FIG. 17 shows examples of priorities set for form indicators.DETAILED DESCRIPTION

[0028] Hereinafter, one or more embodiments of the present disclosure will be described with reference to the drawings. First, the configuration of an exercise guidance system according to an embodiment(s) of the present disclosure will be described with reference to FIG. 1. The exercise guidance system is a system that gives guidance to a user who is running (guidance on user's exercise) to improve his / her running form. As shown in FIG. 1, an exercise guidance system 1 includes a motion sensor device 10, a smartphone 20 and wireless earphone(s) 30.

[0029] The motion sensor device 10 is a wearable terminal that the user of the exercise guidance system 1 uses by wearing it on his / her body (e.g., waist) while running. The smartphone 20 is a portable terminal that the user uses by carrying it while running. The wireless earphone 30 is an ear device that the user uses, like the motion sensor device 10, by wearing it in his / her ear while running. The smartphone 20 is communicably connected by BLE (Bluetooth® Low Energy) with the motion sensor device 10 and the wireless earphone 30.

[0030] Next, a functional configuration of the motion sensor device 10 will be described with reference to FIG. 2. As shown in FIG. 2, the motion sensor device 10 includes a central processing unit (CPU) 11, a random access memory (RAM) 12, a storage 13, a display 14, an operation receiver 15, a sensor unit 16, a sound outputter 17 and a communicator 18. These components of the motion sensor device 10 are connected with one another via a bus 19.

[0031] The CPU 11 controls the components of the motion sensor device 10. The CPU 11 reads a program(s) specified from a system program(s) and application programs stored in the storage 13, loads the read program to the RAM 12, and performs a process among various processes in cooperation with the loaded program. The CPU 11 includes a not-shown timekeeping circuit and obtains the current time measured by the timekeeping circuit. The RAM 12 is a volatile memory and forms a work area where various data and programs are temporarily stored. The storage 13 is composed of, for example, a flash memory, an electrically erasable programmable ROM (EEPROM) or the like. The storage 13 stores the system program and the application programs that are executed by the CPU 11 and data necessary for execution of these programs.

[0032] The display 14 is composed of LED lamps and capable of displaying an ON / OFF state of a power source, a data obtainment state (e.g., whether data is being obtained), a data transmission state (e.g., whether data is being transmitted), an ON / OFF state of a GPS receiver, and so forth. The operation receiver 15 includes a not-shown power button to turn on and off the power source. The CPU 11 controls the components of the motion sensor device 10 on the basis of instructions from this operation receiver 15. The sensor unit 16 includes an acceleration sensor, an angular velocity sensor and the aforementioned GPS receiver and outputs their measurement results to the CPU 11. The sensor unit 16 outputs the measurement results to the CPU 11 at predetermined intervals (e.g., every second, every step of the user, etc.). The measurement results include indicator values (form indicator values) pertaining to form indicators (“Backward Tilt of Trunk”, “Hip Sinking”, “Amount of Breaking”, . . . , and “Ground Contact Time %”, which are shown in FIG. 4) that are learned in (subjects of) lessons, for example, to improve the running form, which will be described later. Alternatively, the CPU 11 may obtain (calculate) form indicator values using data obtained from the sensor unit 16, the data including values of acceleration in directions of three axes as detection results by the acceleration sensor, values of angular velocity in the directions of the three axes as detection results by the angular velocity sensor, and information on the current position (latitude, longitude, altitude, etc.) as detection results by the GPS receiver. The sensor unit 16 may include other sensors in addition to the aforementioned sensors. The sound outputter 17 includes a D / A converter, an amplifier and a speaker. When outputting sound (e.g., voice), the sound outputter 17 converts sound data (e.g., voice data) into analog sound data and outputs the analog sound data through the speaker. The communicator 18 is, for example, a communicator employing a wireless standard, such as Bluetooth, or a wired communicator, such as a USB terminal.

[0033] Next, a functional configuration of the smartphone 20 will be described with reference to FIG. 3. As shown in FIG. 3, the smartphone 20 includes a CPU 21, a RAM 22, a storage 23, a display 24, an operation receiver 25, a sound outputter 26 and a communicator 27. These components of the smartphone 20 are connected with one another via a bus 28.

[0034] The CPU 21 is a processor that reads and executes programs 231 stored in the storage 23 and performs various types of arithmetic processing, thereby controlling the operation of each component of the smartphone 20. Although FIG. 3 shows one CPU 21, the number of CPUs is not limited thereto. Two or more processors, such as CPUs, may be provided, and a plurality of processes that is performed by the CPU 21 in this embodiment may be divided among the two or more processors. The RAM 22 provides a working memory space for the CPU 21 and stores temporary data. The storage 23 stores various data, such as a guidance content database 233 and a running database 234 as well as the programs 231 and a running application 232 that are executed by the CPU 21.

[0035] The programs 231 are stored in the storage 23 in the form of computer-readable program code. The running application 232 is an application for recording running data, such as running track, running distance, running time, pace, pitch and the aforementioned form indicator values, while the user is running. These running data are successively obtained from the motion sensor device 10 while the user is running. The running application 232 has a running guidance function (running form guidance mode) that gives the user who is running guidance on his / her running (exercise) (guidance to improve the running form). In the running database 234, the user's running data recorded during his / her running using the running application 232 is stored.

[0036] In the guidance content database 233, guidance contents that are used in the aforementioned running guidance function (running form guidance mode) are stored. More specifically, as shown in FIG. 4, in the guidance content database 233, guidance contents corresponding to 15 types of lesson (lesson IDs of “001” to “015”) that the user can take in the running guidance function are stored. In the guidance content database 233, reference values for indicator values (form indicator values) pertaining to the form indicators, which are subjects of lessons, are set.

[0037] As shown in FIG. 12, each lesson is composed of four parts; a check part, a learning part, a drill part and a test part (including a first test part and a second test part). In each guidance content in the guidance content database 233, a content for the check part, a content for the learning part, a content for the drill part and a content for the test part are stored. The check part is a part in which the CPU 21 grasps the current state of the running form of the user. More specifically, in the check part, the user is asked to run, and on the basis of a form indicator value measured by the motion sensor device 10 during this running, the current state of the running form of the user is grasped. Then, in a result feedback period following the check part, the current state of the running form of the user is fed back to the user.

[0038] The learning part is a part that comes after the check part and in which the user learns the running form on the basis of the current state of his / her running form. More specifically, in the learning part, a voice (guidance content or first guidance content) for the user to learn the running form is output. In the learning part, as in the check part, the user is asked to run, and a form indicator value measured by the motion sensor device 10 during this running is obtained. Then, in a result feedback period following the learning part, the improvement rate of the form indicator value, the achievement rate based on a target value, and so forth are fed back to the user.

[0039] The drill part is a part that comes after the learning part, i.e., after the user learns (understands in his / her head) the running form, and in which the user actually moves his / her body and understands the running form. More specifically, in the drill part, a voice (guidance content or first guidance content) for the user to understand how to move his / her body, for example, with a slightly exaggerated movement is output. In the drill part, as in the check part and the learning part, the user is asked to run, and a form indicator value measured by the motion sensor device 10 during this running is obtained. Then, in a result feedback period following the drill part, the improvement rate of the form indicator value, the achievement rate based on the target value, and so forth are fed back to the user.

[0040] The test part is a part that comes after the drill part, i.e., after the user understands how to move his / her body, and in which the user runs and the CPU 21 evaluates how well the user can run. More specifically, in the test part, a voice (guidance content or first guidance content) for the user to review what he / she has learned in the learning part and the drill part is output. In the test part, as in the check part, the learning part and the drill part, the user is asked to run, and a form indicator value measured by the motion sensor device 10 during this running is obtained. Then, in an interim feedback period provided in the middle of the test part and a result feedback period following the test part, the improvement rate of the form indicator value, the achievement rate based on the target value, and so forth are fed back to the user.

[0041] Hereinafter, the guidance content database 233 will be further described. Each guidance content stored in the guidance content database 233 and corresponding to each lesson ID is composed of 30 guidance contents corresponding to combinations of six knowledge levels (described later) and five condition levels (described later). For example, as shown in FIG. 5, the guidance content of “Lesson to Improve “Landing Impact”” corresponding to the lesson ID of “007” is broadly divided into six types of guidance content; the guidance content of “Lesson to Learn Basics of “Landing Impact”” for the knowledge level of “0”, the guidance content of “Lesson 2 to Learn Basics of “Landing Impact”” for the knowledge level of “1”, the guidance content of “Lesson Focusing on “Landing Impact” Drill” for the knowledge level of “2”, the guidance content of “Lesson 2 Focusing on “Landing Impact” Drill” for the knowledge level of “3”, the guidance content of “Review Lesson on “Landing Impact”” for the knowledge level of “4”, and the guidance content of “Review Lesson 2 on “Landing Impact”” for the knowledge level of “5”.

[0042] The guidance content of “Lesson to Learn Basics of “Landing Impact”” for the knowledge level of “0” is designed for users who have no knowledge about “Landing Impact” at all. The guidance content of “Lesson 2 to Learn Basics of “Landing Impact”” for the knowledge level of “1” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” but do not understand enough. The guidance content of “Lesson Focusing on “Landing Impact” Drill” for the knowledge level of “2” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” but have some points that they do not understand. The guidance content of “Lesson 2 Focusing on “Landing Impact” Drill” for the knowledge level of “3” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” but have not been able to reflect the lesson in their movement (running form). The guidance content of “Review Lesson on “Landing Impact”” for the knowledge level of “4” is designed for users who have not taken a lesson (guidance) on “Landing Impact” but can perform correct movement. The guidance content of “Review Lesson 2 on “Landing Impact”” for the knowledge level of “5” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” and can perform correct movement. In other words, each of the 30 guidance contents stored in the guidance content database 233 is a lesson to improve a form indicator (e.g., landing impact) in which user's body movement (form) in running is evaluated, and has a content(s) suitable for the user's knowledge level about the form indicator. More specifically, guidance contents for the knowledge level of “0” are guidance contents for the novice (starter) level, guidance contents for the knowledge level of “1” are guidance contents for the beginner level, guidance contents for the knowledge level of “2” are guidance contents for the beginner-to-intermediate level, guidance contents for the knowledge level of “3” are guidance contents for the intermediate level, guidance contents for the knowledge level of “4” are guidance contents for the intermediate-to-advanced level, and guidance contents for the knowledge level of “5” are guidance contents for the advanced level. In other words, the higher the knowledge level, the higher the level of guidance content.

[0043] Each of the six types of guidance content described above is divided into five types of guidance content for condition levels of “Very Good”, “Good”, “Neither Good Nor Bad”, “Bad” and “Very Bad”. For example, as shown in FIG. 5, the guidance content of “Lesson to Learn Basics of “Landing Impact”” for the knowledge level of “0” is divided into the guidance content of “Lesson to Learn Basics of “Landing Impact” Very Hard” for the condition level of “Very Good”, the guidance content of “Lesson to Learn Basics of “Landing Impact”_Hard” for the condition level of “Good”, the guidance content of “Lesson to Learn Basics of “Landing Impact” Normal” for the condition level of “Neither Good Nor Bad”, the guidance content of “Lesson to Learn Basics of “Landing Impact”_Easy” for the condition level of “Bad”, and the guidance content of “Lesson to Learn Basics of “Landing Impact”_Very Easy” for the condition level of “Very Bad”. As shown in FIG. 12, each guidance content is composed of multiple voice files that are provided (output) in a check part period Va, a result feedback period Vb on the check part, a learning part period Vc, a result feedback period Vd on the learning part, a drill part period Ve, a result feedback period Vf on the drill part, a first test part period Vg, an interim feedback period Vh, a second test part period Vi, and a result feedback period Vj on the test part.

[0044] Returning to FIG. 3, the display 24 is composed of a liquid crystal display (LCD) or the like, and displays screens in accordance with display control signals from the CPU 21. On the display screen of the display 24, touch sensors are disposed, so that the display 24 functions as a touchscreen operation-and-display means. The operation receiver 25 includes pushbutton switches and the aforementioned touch sensors disposed on the display 24, and receives user's input operations, converts the contents of the operations into electric signals, and outputs the electric signals to the CPU 21. The sound outputter 26 includes a D / A converter, an amplifier and a speaker. When outputting sound (e.g., voice), the sound outputter 26 converts sound data (e.g., voice data) into analog sound data and outputs the analog sound data through the speaker. The communicator 27 is, for example, a communicator employing a wireless standard, such as Bluetooth, or a wired communicator, such as a USB terminal. The communicator 27 performs wireless data communication with the communicator 18 of the motion sensor device 10 and a communicator 37 of the wireless earphone 30 described below, for example.

[0045] Next, a functional configuration of the wireless earphone 30 will be described with reference to FIG. 6. As shown in FIG. 6, the wireless earphone 30 includes a CPU 31, a RAM 32, a storage 33, a display 34, an operation receiver 35, a sound outputter 36 and the aforementioned communicator 37. These components of the wireless earphone 30 are connected with one another via a bus 38.

[0046] The CPU 31 controls the components of the wireless earphone 30. The CPU 31 reads a program(s) specified from a system program(s) and application programs stored in the storage 33, loads the read program to the RAM 32, and performs a process among various processes in cooperation with the loaded program. The RAM 32 is a volatile memory and forms a work area where various data and programs are temporarily stored. The storage 33 is composed of, for example, a flash memory, an EEPROM or the like. The storage 33 stores the system program and the application programs that are executed by the CPU 31 and data necessary for execution of these programs.

[0047] The display 34 is composed of LED lamps and capable of displaying an ON / OFF state of a power source, the remaining life of a battery, and so forth. The operation receiver 35 includes a not-shown power button to turn on and off the power source and a not-shown adjustment button to adjust the level of sound that is output from the sound outputter 36. The CPU 31 controls the components of the wireless earphone 30 on the basis of instructions from this operation receiver 35. The sound outputter 36 includes a D / A converter, an amplifier and a speaker. When outputting sound (e.g., voice), the sound outputter 36 converts sound data (e.g., voice data) into analog sound data and outputs the analog sound data through the speaker. The communicator 37 is, for example, a communicator employing a wireless standard, such as Bluetooth.

[0048] Next, the operation of the exercise guidance system 1 will be described. More specifically, a running form guidance process that is performed by the CPU 21 of the smartphone 20 will be described. This running form guidance process is performed, for example, when the running form guidance mode (running guidance function) is selected from among multiple modes while the running application 232 is running.

[0049] As shown in FIG. 7, when the running form guidance process is started, first, the CPU 21 of the smartphone 20 causes the display 24 to display a lesson selection screen G1 (Step S1). As shown in FIG. 8, in the lesson selection screen G1, message information (e.g., “Select Lesson to Take”) G11 that urges the user to select a lesson to take is displayed at the top of the screen. The lesson selection screen G1 is provided with selection buttons G12 under the message information G11. The selection buttons G12 correspond to selectable lessons. The screen example shown in FIG. 8 shows a state in which a selection button G12 corresponding to “Lesson to Improve “Landing Impact”” is operated. The lesson selection screen G1 is also provided with an enter button G13 and a stop button G14 at the bottom of the screen. The enter button G13 is used for fixing, as the lesson to take (which hereinafter may be referred to as “target lesson”), the lesson selected (e.g., “Lesson to Improve “Landing Impact””) by the selection button (G12) being selected. The stop button G14 is used for stopping the running form guidance mode. When the stop button G14 is operated, the display 24 displays a not-shown home screen of the running application 232.

[0050] Returning to FIG. 7, after performing the process of Step S1, the CPU 21 determines whether the stop button G14 has been operated (Step S2). If the CPU 21 determines in Step S2 that the stop button G14 has been operated (Step S2; YES), the CPU 21 ends the running form guidance process. If the CPU 21 determines in Step S2 that the stop button G14 has not been operated (Step S2; NO), the CPU 21 determines whether operations to select and fix a lesson have been made (Step S3). The operations to select and fix a lesson mean operating one of the selection buttons G12 and then operating the enter button G13. As described above, the buttons G12, G13 are disposed on the lesson selection screen G1.

[0051] If the CPU 21 determines in Step S3 that the operations to select and fix a lesson have not been made (Step S3; NO), the CPU 21 returns to Step S2 and repeats the processes of Step S2 and the subsequent step(s). If the CPU 21 determines in Step S3 that the operations to select and fix a lesson have been made (Step S3; YES), the CPU 21 instructs the user to start running (Step S4). More specifically, the CPU 21 transmits voice data for instructing the user to start running to the wireless earphone 30 via the communicator 27, and causes the sound outputter 36 of the wireless earphone 30 to output a voice based on the voice data (e.g., “In order to grasp current running form, start running”). When the CPU 21 performs the process of Step S4, the motion sensor device 10 is already ready to derive / measure data (running data) such as form indicator values mentioned above. By the CPU 21 performing the process of Step S4, the check part (shown in FIG. 12) of the lesson (e.g., “Lesson to Improve “Landing Impact””) that the user takes starts.

[0052] Next, the CPU 21 determines whether a predetermined time (e.g., five minutes) has elapsed from the completion of the process of Step S4 (Step S5). If the CPU 21 determines in Step S5 that the predetermined time has not elapsed (Step S5; NO), the CPU 21 repeats the process of Step S5 until the predetermined time elapses. If the CPU 21 determines in Step S5 that the predetermined time has elapsed (Step S5; YES), the CPU 21 instructs the user to stop running (Step S6). More specifically, the CPU 21 transmits voice data for instructing the user to stop running to the wireless earphone 30 via the communicator 27, and causes the sound outputter 36 of the wireless earphone 30 to output a voice (e.g., “Stop running”) based on the voice data. By the CPU 21 performing the process of Step S6, the check part (shown in FIG. 12) of the lesson (e.g., “Lesson to Improve “Landing Impact””) that the user is taking finishes. The period from when the instruction to start running is made (and the user actually starts running) until when the predetermined time elapses is the check part period Va (shown in FIG. 12). In this check part period Va, a voice for (corresponding to) this period Va is output from the sound outputter 36 of the wireless earphone 30. More specifically, as shown in FIG. 13 and FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the check part period Va, a voice of “Today, we will give you a lesson on landing impact. First, we will check your current state, so relax and run for five minutes as usual.” The voice data of this voice corresponds to the content for the check part. In other words, the content is obtained from the guidance content database 233 using the instruction to start running as a trigger.

[0053] Next, the CPU 21 obtains a form indicator value pertaining to the form indicator, which is the subject of the lesson that the user is taking (Step S7). More specifically, the CPU 21 obtains, via the communicator 27, a form indicator value pertaining to the form indicator, which is the subject of the lesson that the user is taking, measured between when the CPU 21 instructs the user to start running in Step S4 and when the CPU 21 instructs the user to stop running in Step S6. If the lesson that the user is taking is “Lesson to Improve “Landing Impact””, the CPU 21 obtains a form indicator value pertaining to the form indicator of “Landing Impact” (shown in FIG. 4) as the subject of the lesson.

[0054] Next, the CPU 21 performs a knowledge level determination process (Step S8). As shown in FIG. 9, when the knowledge level determination process is started, the CPU 21 determines whether the form indicator value obtained in Step S7 of the running form guidance process (shown in FIG. 7) satisfies its reference value (shown in FIG. 4) (Step S21). The form indicator value that is used for this determination is the mean of all form indicator values pertaining to the form indicator measured from the start of running in Step S4 to the end of running in Step S6 but not limited thereto. The form indicator value may be the median, the mode or the like. There are two types of form indicator. One type of form indicator is a form indicator whose form indicator value indicates a better state as it is smaller. Examples thereof include “Backward Tilt of Trunk”, “Hip Sinking”, “Amount of Breaking”, “Vertical Movement” and “Landing Impact”. The other type of form indicator is a form indicator whose form indicator value indicates a better state as it is larger. Examples thereof include “Lifting-up of Pelvis” and “Stiffness”. Therefore, in the case of a form indicator whose form indicator value indicates a better state as it is smaller, the CPU 21 determines that the form indicator value pertaining to the form indicator satisfies its reference value if the form indicator value is equal to or less than the reference value, and determines that the form indicator value does not satisfy the reference value if the form indicator value is greater than the reference value. On the other hand, in the case of a form indicator whose form indicator value indicates a better state as it is larger, the CPU 21 determines that the form indicator value pertaining to the form indicate satisfies its reference value if the form indicator value is equal to or greater than its reference value, and determines that the form indicator value does not satisfy the reference value if the form indicator value is less than the reference value.

[0055] If the CPU 21 determines in Step S21 that the form indicator value does not satisfy the reference value (Step S21; NO), the CPU 21 determines how many times the user has taken this target lesson (Step S22). The number of times the user has taken the target lesson is stored in the running database 234. If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is zero (Step S22; Zero), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “0” (Step S23). If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is one (Step S22; Once), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “1” (Step S24). If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is two (Step S22; Twice), the CPU 21 determines that the knowledge level of the user about the form indicator that is the subject of the target lesson is “2” (Step S25). If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is three or more (Step S22; Three times or more), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “3” (Step S26). After performing the process of Step S23, Step S24, Step S25 or Step S26, the CPU 21 returns to the running form guidance process.

[0056] If the CPU 21 determines in Step S21 that the form indicator value satisfies the reference value (Step S21; YES), the CPU 21 determines how many times the user has taken this target lesson (Step S27). If the CPU 21 determines in Step S27 that the number of times the user has taken the target lesson is zero (Step $27; Zero), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “4” (Step S28). If the CPU 21 determines in Step S27 that the number of times the user has taken the target lesson is once or more (Step S27; Once or more), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “5” (Step $29). After performing the process of Step S28 or Step S29, the CPU 21 returns to the running form guidance process. In other words, the knowledge level is a value that is set on the basis of the form indicator value pertaining to the form indicator and the number of times the user has taken the target lesson, the subject of which is the form indicator.

[0057] Returning to FIG. 7, after performing the knowledge level determination process, the CPU 21 performs a condition level determination process (Step S9). As shown in FIG. 10, when the condition level determination process is started, the CPU 21 determines whether the user's running records (running data) of the last three times (of running) are stored in the running database 234 (Step S41). If the CPU 21 determines in Step S41 that the running records (running data) of the last three times are not stored in the running database 234 (Step S41; NO), the CPU 21 determines that the condition level of the user is “Neither Good Nor Bad” (Step S50). The CPU 21 then returns to the running form guidance process.

[0058] If the CPU 21 determines in Step S41 that the running records (running data) of the last three times are stored in the running database 234 (Step S41; YES), the CPU 21 derives, on the basis of the running records, the mean (B) of the average paces in a period of beginning of running of the last three times (Step S42). This “period of beginning of running” is, for example, five minutes (equivalent to the period of the check part) from the start of running. Next, the CPU 21 derives the average pace (A) in the period of beginning of running of this time (Step S43). In other words, in Step S43, the CPU 21 derives the average pace (A) of the user's running in the period of the check part (shown in FIG. 12).

[0059] Next, the CPU 21 compares the average pace (A) in the period of beginning of running of this time derived in Step S43 with the mean (B) of the average paces in the period of beginning of running of the last three times derived in Step S42 (Step S44). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is 30 seconds or more faster than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; 30 seconds or more faster), the CPU 21 determines that the condition level of the user is “Very Good” (Step S45). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is more than 10 seconds but less than 30 seconds faster than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; more than 10 seconds but less than 30 seconds faster), the CPU 21 determines that the condition level of the user is “Good” (Step S46). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is ±10 seconds compared to the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; ±10 seconds), the CPU 21 determines that the condition level of the user is “Neither Good Nor Bad” (Step S47). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is more than 10 seconds but less than 30 seconds slower than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; more than 10 seconds but less than 30 seconds slower), the CPU 21 determines that the condition level of the user is “Bad” (Step S48). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is 30 seconds or more slower than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; 30 seconds or more slower), the CPU 21 determines that the condition level of the user is “Very Bad” (Step S49). After performing the process of Step S45, Step S46, Step S47, Step S48 or Step S49, the CPU 21 returns to the running form guidance process.

[0060] Returning to FIG. 7, after performing the condition level determination process, the CPU 21 obtains a guidance content to be provided to the user in the target lesson (Step S10). For example, if the target lesson is “Lesson to Improve “Landing Impact””, the knowledge level of the user determined in Step S8 is “1”, and the condition level of the user determined in Step S9 is “Good”, the CPU 21 obtains “Lesson 2 to Learn Basics of “Landing Impact”_Hard” from the guidance content database 233 (shown in FIG. 5) as the guidance content to be provided to the user. As another example, if the target lesson is “Lesson to Improve “Landing Impact””, the knowledge level of the user determined in Step S8 is “3”, and the condition level of the user determined in Step S9 is “Bad”, the CPU 21 obtains “Lesson 2 Focusing on “Landing Impact” Drill Easy” from the guidance content database 233 (shown in FIG. 5) as the guidance content to be provided to the user.

[0061] Next, the CPU 21 performs a guidance content provision process on the basis of the guidance content obtained in Step S10 (Step S11). As shown in FIG. 11, when the guidance content provision process is started, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vb on the check part (shown in FIG. 12), a voice for the result feedback period Vb on the basis of the guidance content obtained in Step S10 (Step S61). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vb on the check part, a voice of “You seem in a good condition today. Go for the highest achievement rate ever. Today's reference value is 25.0.” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vb on the check part, a voice of “You seem in a bad condition today. Take it easy and do the best you can today. Today's reference value is 25.0.”

[0062] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the learning part period Vc (shown in FIG. 12), a voice for this period Vc (Step S62). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the learning part period Vc, a voice of “In this lesson, you will run while learning the basics of landing impact again. There are three main causes of high landing impact. The first one is landing on the heel, the second one is not shifting the weight properly and putting the brakes on yourself, and the third one is . . . . Run for a while, keeping in mind what you have learned . . . .” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the learning part period Vc, a voice of “In this lesson, you will run while learning landing impact in more depth. You will learn a technique for shifting the weight from stable landing. We will first explain how to swing down below the knees . . . . Run for a while, keeping in mind what you have learned . . . .”

[0063] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vd on the learning part (shown in FIG. 12), a voice for this period Vd (Step S63). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vd on the learning part, a voice of “You showed 7% improvement. Go for more improvement today.” The “7% improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the learning part period Vc. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vd on the learning part, a voice of “You showed no improvement. Take it easy and run comfortably today. It is important to run with awareness even if you cannot get a result.” The “no improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the learning part period Vc.

[0064] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the drill part period Ve (shown in FIG. 12), a voice for this period Ve (Step S64). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the drill part period Ve, a voice of “In this drill, you will try the basic drill again. First, for learning posture, move to a safe place where you can stop . . . . Run for a while, keeping in mind the feelings you had during the drill . . . ” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the drill part period Ve, a voice of “In this drill, you will try a technical drill. First, for learning steps, move to a safe place where you can get a straight line of about 20 m . . . . Run for a while, keeping in mind the feelings you had during the drill . . . .”

[0065] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vf on the drill part (shown in FIG. 12), a voice for this period Vf (Step S65). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vf on the drill part, a voice of “You showed 10% improvement. Go for more improvement today.” The “10% improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the drill part period Ve. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vf on the drill part, a voice of “You showed 5% improvement. Take it easy and run slowly with awareness today.” The “5% improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the drill part period Ve.

[0066] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the first test part period Vg (shown in FIG. 12), a voice for this period Vg (Step S66). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the first test part period Vg, a voice of “From here on, run for an achievement rate of 90%, keeping in mind what you have learned today. So, start. First of all, it is important to keep straightening your back up . . . .” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the first test part period Vg, a voice of “From here on, run for an achievement rate of 80%, keeping in mind what you have learned today. So, start. First of all, lifting your legs up is . . . .”

[0067] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the interim feedback period Vh (shown in FIG. 12), a voice for this period Vh (Step S67). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the interim feedback period Vh, a voice of “The achievement rate so far is 78%. Focus on the posture and land softly on the middle of the foot.” The “achievement rate so far is 78%” is information derived on the basis of the form indicator value pertaining to “Landing Impact” measured in the first test part period Vg and the reference value for “Landing Impact”. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the interim feedback period Vh, a voice of “The achievement rate so far is 65%. Focus on the speed at which you return your feet to match the road speed, but don't push yourself hard.” The “achievement rate so far is 65%” is information derived on the basis of the form indicator value pertaining to “Landing Impact” measured in the first test part period Vg and the reference value for “Landing Impact”.

[0068] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the second test part period Vi (shown in FIG. 12), a voice for this period Vi (Step S68). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the second test part period Vi, a voice of “Run one more time for an achievement rate of 90%, keeping in mind what you have learned today. So, start. First of all, it is important to keep straightening your back up.” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the second test part period Vi, a voice of “Run one more time for an achievement rate of 80%, keeping in mind what you have learned today. So, start. First of all, lifting your legs up is . . . .”

[0069] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vj on the test part (shown in FIG. 12), a voice for this period Vj (Step S69). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vj on the test part, a voice of “It's time for a cool-down. Walk and get your breathing under control . . . . Let's take a look at today's results. The achievement rate is 88% with respect to the reference value of 25.0. You did not reach the goal today. Keep trying to achieve the goal.” The “achievement rate is 88%” output by the voice is information derived on the basis of the form indicator value(s) pertaining to “Landing Impact” measured in the periods from the first test part period Vg to the interim feedback period Vh or from the first test part period Vg through the interim feedback period Vh to the second test part period Vi and the reference value for “Landing Impact”. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vj on the test part, a voice of “It's time for a cool-down. Walk and get your breathing under control . . . . Let's take a look at today's results. The achievement rate is 69% with respect to the reference value of 25.0. You did not reach the goal today. Take it easy and make steady improvement.” The “achievement rate is 69%” is information derived on the basis of the form indicator value(s) pertaining to “Landing Impact” measured from the first test part period Vg to the interim feedback period Vh or from the first test part period Vg through the interim feedback period Vh to the second test part period Vi and the reference value for “Landing Impact”. After performing the process of Step S69, the CPU 21 returns to the running form guidance process. The CPU 21 then ends the running form guidance process.

[0070] As shown in FIG. 11 and FIG. 12, the CPU 21 performs the process in the first test part period Vg, the process in the interim feedback period Vh, the process in the second test part period Vi and the process in the result feedback period Vj in this order, but the present disclosure is not limited thereto. For example, after performing the process in the first test part period Vg, the CPU 21 may perform the process in the result feedback period Vj without performing the process in the second test part period Vi. In this case, the CPU 21 may perform the process in the second test part period Vi if an indicator value measured in the first test part period Vg satisfies a predetermined condition, and not perform the process in the second test part period Vi if the indicator value measured in the first test part period Vg does not satisfy the predetermined condition. To be more specific, a not-shown condition determination step may be added between Step S66 and Step S67. Examples of the predetermined condition include a condition that an indicator value (heart rate) measured by a heart rate sensor included in the sensor unit 16 is equal to or less than a predetermined value, and a condition that a form indicator value pertaining to a predetermined form indicator (“Landing Impact” in this embodiment) among the form indicators is equal to or less than a predetermined value (or equal to or greater than a predetermined value depending on the type of form indicator). If the CPU 21 determines to skip the second test part period Vi on the basis of the indicator value measured in the first test part period Vg, the CPU 21 may skip the interim feedback period Vh too. That is, after performing the process in the first test part period Vg, the CPU 21 may perform the process in the result feedback period Vj. Thus, if the CPU 21 determines, from the measured indicator value, that the user seems to still have enough strength, the CPU 21 takes the second test part period Vi next to the interim feedback period Vh, thereby being able to provide, to the user, information beneficial for the user efficiently. In the same manner, after the second test part period Vi, a not-shown third test part period may be provided on the basis of the indicator value measured in the second test part period Vi. If the third test part period is provided, a not-shown interim feedback period, which is similar to the interim feedback period Vh, may also be provided between the second test part period Vi and the third test part period.

[0071] The conventional running form determination device disclosed in JP H2-203842 A determines whether the running form is good numerically, and therefore has a problem that the determination result is difficult to understand. Thus, this running form determination device cannot make use of the determination result or improve the running form efficiently.

[0072] In contrast, the CPU 21 of the smartphone 20 of this embodiment selects (obtains) a content guidance pertaining to a predetermined form indicator from among guidance contents about movement of the body of a user in running (exercise). Further, the CPU 21 obtains a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is running (doing the exercise). Further, the CPU 21 provides the selected guidance content to the user who is running, by performing, with respect to each guidance timing of guidance timings (check part, learning part, drill part and test part) during running, a series of processes of providing a first guidance content (e.g., content for the check part, i.e., voice for the check part period Va) corresponding to each guidance timing and providing a second guidance content (e.g., content that is provided in the result feedback period Vb, i.e., voice for the result feedback period Vb) corresponding to the result of the form indicator value that the CPU 21 obtains while providing the first guidance content, in the order named. Thus, with respect to each guidance timing, the smartphone 20 provides the first guidance content to the user, thereby giving the user a lesson (guidance) on the movement of the body of the user in running, and provides the second guidance content to the user, thereby feeding back, to the user, the result of the user moving his / her body under the guidance, and therefore can improve the running form efficiently.

[0073] Further, the CPU 21 of the smartphone 20 provides the first guidance content and the second guidance content, the first guidance content corresponding to each guidance timing of the guidance timings of the check part in which the CPU 21 grasps the current state of the movement of the body of the user, the learning part that comes after the check part and in which the user learns how to move the body of the user based on the current state of the movement of the body of the user, the drill part that comes after the learning part and in which the user actually moves the body and understands how to move the body, and the test part that comes after the drill part and in which the user runs and the CPU 21 evaluates the movement of the body of the user in the running (exercise). Thus, the smartphone 20 gives the user guidance in four parts; the check part, the learning part, the drill part and the test part, and therefore can improve the running form even more efficiently.

[0074] Further, the CPU 21 of the smartphone 20 obtains the form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is running (doing the exercise) and derived based on measured data obtained by the motion sensor device 10 (motion sensor) worn on the body of the user performing sampling. Thus, the smartphone 20 can obtain an accurate form indicator value, and therefore can give the user appropriate feedback in providing the second guidance content.

[0075] Further, the test part is provided with at least one interim feedback period (Vh) (shown in FIG. 12) in which interim feedback included in the first guidance content is given to the user, before a result feedback period (Vj) (shown in FIG. 12) in which result feedback included in the second guidance content is given to the user. Therefore, the smartphone 20 allows the user to check, in the interim feedback period Vh, how his / her running form has been changed and to easily adjust the running form.

[0076] Further, the CPU 21 of the smartphone 20 determines the knowledge level of the user about running (exercise), and based on the determined knowledge level, selects (obtains) the guidance content for the knowledge level. Thus, in providing the guidance content, the smartphone 20 provides the guidance content for the knowledge level of the user about running, and therefore can provide, to the user, the guidance content beneficial to the user.

[0077] Next, a modification of the running form guidance process (shown in FIG. 7) will be described. The running form guidance process according to this modification is characterized in that the CPU 21 determines a form indicator to be improved from form indicator values pertaining to form indicators measured in the check part, and provides, to the user, a guidance content corresponding to the determined form indicator.

[0078] As shown in FIG. 15, when the running form guidance process according to the modification is started, first, the CPU 21 of the smartphone 20 instructs the user to start running (Step S101). More specifically, the CPU 21 transmits voice data for instructing the user to start running to the wireless earphone 30 via the communicator 27. The CPU 21 then causes the sound outputter 36 of the wireless earphone 30 to output a voice (e.g., “In order to determine a form indicator to be improved, start running.”) based on the voice data. When the CPU 21 performs the process of Step S101, the motion sensor device 10 is already ready to derive / measure data (running data) such as form indicator values mentioned above. By the CPU 21 performing the process of Step S101, the check part Va (shown in FIG. 12) of the lesson (running form guidance) that the user takes starts.

[0079] Next, the CPU 21 determines whether a predetermined time (e.g., five minutes) has elapsed from the completion of the process of Step S101 (Step S102). If the CPU 21 determines in Step S102 that the predetermined time has not elapsed (Step S102; NO), the CPU 21 repeats the process of Step S102 until the predetermined time elapses. If the CPU 21 determines in Step S102 that the predetermined time has elapsed (Step S102; YES), the CPU 21 instructs the user to stop running (Step S103). More specifically, the CPU 21 transmits voice data for instructing the user to stop running to the wireless earphone 30 via the communicator 27, and causes the sound outputter 36 of the wireless earphone 30 to output a voice (e.g., “Stop running”) based on the voice data. By the CPU 21 performing the process of Step S103, the check part Va (shown in FIG. 12) of the lesson (running form guidance) that the user is taking finishes.

[0080] Next, the CPU 21 performs an improvement-required form indicator determination process (Step S104). As shown in FIG. 16, when the improvement-required form indicator determination process is started, the CPU 21 sets the value of a variable “X” to the initial value of “1”, and obtains a form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first (highest) priority (Priority_1) (X=1) (shown in FIG. 17) (Step S121). Next, the CPU 21 determines whether the form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) obtained in Step S121 satisfies its reference value of “1.0” (Step S122). As to a form indicator value pertaining to a certain form indicator, if the form indicator value is equal to or less than its reference value, it is determined that the exercise form is proper in terms of the form indicator and accordingly it is determined that the form indicator value satisfies the reference value. As to a form indicator value of another certain form indicator, if the form indicator value is equal to or greater than its reference value, it is determined that the exercise form is proper in terms of the form indicator and accordingly it is determined that the form indicator value satisfies the reference value. As a specific example, in the case of a form indicator value pertaining to “Backward Tilt of Trunk”, it is determined that the form indicator value satisfies its reference value if the form indicator value is equal to or less than “1.0”, which is the reference value for “Backward Tilt of Trunk”. As another specific example, in the case of a form indicator value pertaining to “Kickout Acceleration”, it is determined that the form indicator value satisfies its reference value if the form indicator value is equal to or greater than “45”, which is the reference value for “Kickout Acceleration”.

[0081] If the CPU 21 determines in Step S122 that the form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) does not satisfy its reference value of “1.0” (Step S122; NO), the CPU 21 determines the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) as the form indicator to be improved (Step S125). That is, in this case, the check part and the subsequent parts of the lesson are conducted with the form indicator of “Backward Tilt of Trunk” as the form indicator to be improved.

[0082] If the CPU 21 determines in Step S122 that the form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) satisfies its reference value of “1.0” (Step S122; YES), the CPU 21 increases the value of “X” in “Priority X” by one, and obtains a form indicator value pertaining to the form indicator of “Hip Sinking” having the second priority (Priority_2) (shown in FIG. 17) (Step S123). The CPU 21 determines whether the value of “X” increased by one in Step S123 is 16 (Step S124).

[0083] If the CPU 21 determines in Step S124 that the value of “X” increased by one in Step S123 is not 16 (Step S124; NO), the CPU 21 returns to Step $122 and repeats the processes of Step S122 and the subsequent steps. For example, if the CPU 21 determines in Step S122 that the form indicator value pertaining to the form indicator of “Landing Impact” having the seventh priority (Priority_7) does not satisfy its reference value of “25.0” (Step S122; NO), the CPU 21 determines the form indicator of “Landing Impact” having the seventh priority (Priority_7) as the form indicator to be improved (Step S125). That is, in this case, the check part and the subsequent parts of the lesson are conducted with the form indicator of “Landing Impact” as the form indicator to be improved.

[0084] If the CPU 21 determines in Step S124 that the value of “X” increased by one in Step S123 is 16 (Step S124; YES), namely, determines that the form indicator values pertaining to the form indicators having the first priority (Priority_1) to the 15th priority (Priority_15) all satisfy their respective reference values, the CPU 21 ends the improvement-required form indicator determination process without determining the form indicator to be improved, and returns to the running form guidance process (shown in FIG. 15).

[0085] Returning to FIG. 15, the CPU 21 determines whether the form indicator to be improved has been determined in the improvement-required form indicator determination process (Step S105). If the CPU 21 determines in Step S105 that the form indicator to be improved has been determined (Step S105; YES), the CPU 21 performs the knowledge level determination process (Step S106), the condition level determination process (Step S107), the process of obtaining a guidance content to be provided to the user (Step S108) and the guidance content provision process (Step S109), and then ends the running form guidance process. Since the processes of Step S106 to Step S109 are the same as the processes of Step S8 to Step S11 described with reference to FIG. 7, respectively, their detailed descriptions will be omitted.

[0086] If the CPU 21 determines in Step S105 that the form indicator to be improved has not been determined (Step S105; NO), namely, determines that the form indicator values pertaining to the form indicators having the first priority (Priority_1) to the 15th priority (Priority_15) all satisfy their respective reference values, the CPU 21 notifies the user of the end of the running form guidance (Step S110). More specifically, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output a voice indicating the end of the running form guidance (e.g., “Since the form indicator to be improved is not present, the running form guidance will be ended”). The CPU 21 then ends the running form guidance process. Although in the above, if the CPU 21 determines in Step S105 that the form indicator to be improved has not been determined (Step S105; NO), the CPU 21 ends the running form guidance, the present disclosure is not limited thereto. For example, if the CPU 21 determines in Step S105 that the form indicator to be improved has not been determined (Step S105; NO), the CPU 21 may refer to form indicator values (e.g., form indicator values pertaining to the 15 types of form indicator shown in FIG. 17) in user's previous (e.g., last) running that are recorded / stored in the running database 234, compare these with their respective reference values, and determine, as the form indicator to be improved, a form indicator whose form indicator value is farthest from its reference value. In this case, on the basis of the form indicator thus determined, the CPU 21 performs the processes of Steps S106 to S109 shown in FIG. 15.

[0087] Those described in the above embodiment are not limitations but mere examples of the exercise guidance device, the exercise guidance method and the program stored in the storage medium according to the present disclosure. For example, although in the above embodiment, the contents of a guidance content (e.g., “Lesson 2 to Learn Basics of “Landing Impact”_Hard”) that is provided in a lesson is determined on the basis of the knowledge level and the condition level of the user, this determination method is a mere example. For example, the contents of a guidance content that is provided in a lesson may be determined in accordance with the state of a form indicator value(s) pertaining to a form indicator(s) other than the form indicator that is the subject of the lesson. For example, a form indicator value pertaining to “Landing Impact” not satisfying its reference value may be partly due to a form indicator value pertaining to “Backward Tilt of Trunk” and / or a form indicator value pertaining to “Hip Sinking” not satisfying its / their reference value(s). Therefore, for example, if the form indicator as the subject of the lesson is “Landing Impact”, and the form indicator value pertaining to “Backward Tilt of Trunk” and the form indicator value pertaining to “Hip Sinking” do not satisfy their respective reference values, the guidance content having the contents that refer to these form indicators too may be determined as the guidance content that is provided in the lesson. On the other hand, if the form indicator value pertaining to “Backward Tilt of Trunk” and the form indicator value pertaining to “Hip Sinking” satisfy their respective reference values, the guidance content having the contents that do not refer to these form indicators may be determined as the guidance content that is provided in the lesson. The relationship between the form indicator of “Landing Impact” whose indicator value does not satisfy its reference value and another form indicator(s) (e.g., “Backward Tilt of Trunk”, “Hip Sinking”, etc.) that could be the cause may be stored in advance in a not-shown database in the storage 23.

[0088] Further, although in the above embodiment, when providing the guidance content in the guidance content provision process (Step S11) of the running form guidance process (shown in FIG. 7) and mentioning the advancement rate of the form indicator value of the subject of the lesson as shown in FIG. 13 and FIG. 14, the CPU 21 derives the achievement rate using the reference value (default reference value) set in the guidance content database 233 (shown in FIG. 4), this reference value may be changeable. More specifically, if the mean (which hereinafter may be referred to as “target indicator mean”) of the form indicator values pertaining to the form indicator as the subject of the lesson in the period of beginning of running of the last three times does not satisfy the default reference value, the CPU 21 sets the reference value that is used for deriving the achievement rate to the default reference value. On the other hand, if the mean of the form indicator values pertaining to the form indicator as the subject of the lesson in the period of beginning of running of the last three times satisfies the default reference value, the CPU 21 sets the reference value that is used for deriving the achievement rate to a reference value calculated by Formula (1) or Formula (2) below.<For Form Indicator Whose Form Indicator Value Indicates Better State as it is Larger>Reference⁢ Value=Target⁢ Indicator⁢ Mean+(Target⁢ Indicator⁢ Mean×Intensity⁢ Coefficient×Condition⁢ Coefficient)Formula⁢ (1)<For Form Indicator Whose Form Indicator Value Indicates Better State as it is Smaller>Reference⁢ Value=Target⁢ Indicator⁢ Mean-(Target⁢ Indicator⁢ Mean×Intensity⁢ Coefficient×Condition⁢ Coefficient)Formula⁢ (2)The “Intensity Coefficient” is set for user's desired intensity that is set on the basis of a user operation. If the user desires “Hard”, the intensity coefficient is set to “0.6”. If the user desires “Normal”, the intensity coefficient is set to “0.3”. If the user desires “Easy”, the intensity coefficient is set to “0.1”. As the “Condition Coefficient”, a coefficient for the condition level determined in the condition level determination process (shown in FIG. 10) is set. If the condition level determined in the condition level determination process is “Very Good”, a condition coefficient of “1.2” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “0.7” is set. If the determined condition level is “Good”, a condition coefficient of “1.1” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “0.8” is set. If the determined condition level is “Neither Good Nor Bad”, a condition coefficient of “1.0” is set. If the determined condition level is “Bad”, a condition coefficient of “0.8” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “1.1” is set. If the determined condition level is “Very Bad”, a condition coefficient of “0.7” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “1.2” is set.

[0090] There are two types of form indicator as subjects of lessons; form indicators whose form indicator values are likely to fluctuate and form indicators whose form indicator values are unlikely to fluctuate. Therefore, in the case where the reference value is changeable as described above, the reference value may be calculated in accordance with the form indicator as the subject of the lesson by using a calculation formula suitable for the form indicator.

[0091] Further, although in the above embodiment, the guidance content obtained in Step S10 of the running form guidance process (shown in FIG. 7) is provided in each period thereafter, i.e., from the result feedback period Vb on the check part, the type of guidance content to be provided may be changed, for example, part by part. More specifically, in the learning part period Vc, a form indicator value pertaining to a form indicator as the subject of a lesson is measured, and if the form indicator value measured in the learning part period Vc shows 5% or more improvement compared to the form indicator value measured in the check part period Va, the knowledge level is raised by two levels (e.g., if the current knowledge level is “1”, it is raised to “3”). As another example, if the form indicator value measured in the learning part period Vc shows more than 0% but less than 5% improvement compared to the form indicator value measured in the check part period Va, the current knowledge level is raised by one level. As another example, if the form indicator value measured in the learning part period Vc shows no (0% or less) improvement compared to the form indicator value measured in the check part period Va, the current knowledge level maintains the status quo. In the case where there is a change in the knowledge level, the guidance content to be provided to the user is reobtained on the basis of the knowledge level after the change and the condition level determined in the condition level determination process (Step S9). Then, the obtained guidance content is provided to the user in the result feedback period Vd on the learning part and in the drill part period Ve. The same process may be performed in the drill part period Ve, and if there is a change in the knowledge level, the guidance content to be provided to the user is reobtained on the basis of the knowledge level after the change and the condition level determined in the condition level determination process (Step S9). Then, the obtained guidance content is provided to the user in each period thereafter, i.e., from the result feedback period Vf on the drill part.

[0092] Further, although in the running form guidance process (shown in FIG. 7) of the above embodiment, the guidance content for the knowledge level and the condition level of the user is obtained from the guidance content database 233, the guidance content to be provided to the user may be generated, for example, by inputting the knowledge level, the condition level and the running data of the user into a predetermined machine-learned model. This machine-learned model is a model machine-learned with training data (training information) in each of which data of the knowledge level and the condition level of a user both determined in the check part of a lesson, the contents of a guidance content provided to the user in each part (learning part, drill part, test part) of the lesson and running data of the user in each part of the lesson are associated with, as a correct answer, the achievement rate of the form indicator value pertaining to the form indicator as the subject of the lesson with respect to its reference value.

[0093] Further, although in the above embodiment, result feedback is given to the user when the learning part finishes as shown in FIG. 12, interim feedback may be given to the user in the middle of the learning part as in the test part. The same may apply to the drill part. Further, when providing the guidance content in the test part and the drill part, the CPU 21 may cause not only the sound outputter 36 of the wireless earphone 30 to output the voices of the guidance content but also the display 24, which is included in the smartphone 20, to output moving images of the guidance content.

[0094] Further, although in the above embodiment, the exercise guidance system 1 is composed of the motion sensor device 10, the smartphone 20 and the wireless earphone 30, the exercise guidance system 1 may be composed of, for example, the motion sensor device 10 and the wireless earphone 30. In this case, the motion sensor device 10 is configured to be communicably connected with the wireless earphone 30 directly by BLE. In addition, the CPU 11 of the motion sensor device 10 is configured to perform the processes shown by the flowcharts in FIG. 7, FIG. 9, FIG. 10 and FIG. 11.

[0095] It is a matter of course that the detailed configuration and detailed operation of each component of the motion sensor device 10, the smartphone 20 and the wireless earphone 30 of the above embodiment can be changed as appropriate without departing from the scope of the present disclosure.

Examples

Embodiment Construction

[0028]Hereinafter, one or more embodiments of the present disclosure will be described with reference to the drawings. First, the configuration of an exercise guidance system according to an embodiment(s) of the present disclosure will be described with reference to FIG. 1. The exercise guidance system is a system that gives guidance to a user who is running (guidance on user's exercise) to improve his / her running form. As shown in FIG. 1, an exercise guidance system 1 includes a motion sensor device 10, a smartphone 20 and wireless earphone(s) 30.

[0029]The motion sensor device 10 is a wearable terminal that the user of the exercise guidance system 1 uses by wearing it on his / her body (e.g., waist) while running. The smartphone 20 is a portable terminal that the user uses by carrying it while running. The wireless earphone 30 is an ear device that the user uses, like the motion sensor device 10, by wearing it in his / her ear while running. The smartphone 20 is communicably connected ...

REFERENCE TO RELATED APPLICATIONS

[0001] This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 2024-161073, filed on Sep. 18, 2024, the entire contents, including the description, claims, abstract and drawings, of which are incorporated herein by reference.TECHNICAL FIELD

[0002] The present disclosure relates to an exercise guidance device, an exercise guidance method and a storage medium.DESCRIPTION OF RELATED ART

[0003] There is disclosed, for example, in JP H2-203842 A a conventional running determination device that detects acceleration of movement of the body of a user in the up-down direction and acceleration of movement of the body of the user in the front-back direction and determines whether his / her running form is good.SUMMARY OF THE INVENTION

[0004] According to an aspect of the present disclosure, there is provided an exercise guidance device including:

[0005] a memory that stores a program; and

[0006] at least one processor that executes the program,

[0007] wherein the processor

[0008] obtains a guidance content pertaining to a predetermined form indicator from among guidance contents about a movement of a body of a user in exercise,

[0009] obtains a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise, and

[0010] provides the obtained guidance content to the user who is doing the exercise, by performing, with respect to each guidance timing of guidance timings during the exercise, a series of processes of providing a first guidance content corresponding to the each guidance timing and providing a second guidance content corresponding to a result of the form indicator value that the processor obtains while providing the first guidance content, in order named.BRIEF DESCRIPTION OF DRAWINGS

[0011] FIG. 1 is a block diagram showing an exercise guidance system according to an embodiment(s) of the present disclosure.

[0012] FIG. 2 is a block diagram m showing a functional configuration of a motion sensor device.

[0013] FIG. 3 is a block diagram showing a functional configuration of a smartphone.

[0014] FIG. 4 shows examples of contents of a guidance content database.

[0015] FIG. 5 shows examples of contents of the guidance content database.

[0016] FIG. 6 is a block diagram showing a functional configuration of a wireless earphone(s).

[0017] FIG. 7 is a flowchart showing a control procedure for a running form guidance process.

[0018] FIG. 8 shows an example of a lesson selection screen.

[0019] FIG. 9 is a flowchart showing a control procedure for a knowledge level determination process.

[0020] FIG. 10 is a flowchart showing a control procedure for a condition level determination process.

[0021] FIG. 11 is a flowchart showing a control procedure for a guidance content provision process.

[0022] FIG. 12 shows the structure of a lesson that a user can take in a running form guidance mode.

[0023] FIG. 13 shows examples of voice contents of Lesson 2 to Learn Basics of “Landing Impact”_Hard.

[0024] FIG. 14 shows examples of voice contents of Lesson 2 Focusing on “Landing Impact” Drill Easy.

[0025] FIG. 15 is a flowchart showing a control procedure for the running form guidance process according to a modification.

[0026] FIG. 16 is a flowchart showing a control procedure for an improvement-required form indicator determination process.

[0027] FIG. 17 shows examples of priorities set for form indicators.DETAILED DESCRIPTION

[0028] Hereinafter, one or more embodiments of the present disclosure will be described with reference to the drawings. First, the configuration of an exercise guidance system according to an embodiment(s) of the present disclosure will be described with reference to FIG. 1. The exercise guidance system is a system that gives guidance to a user who is running (guidance on user's exercise) to improve his / her running form. As shown in FIG. 1, an exercise guidance system 1 includes a motion sensor device 10, a smartphone 20 and wireless earphone(s) 30.

[0029] The motion sensor device 10 is a wearable terminal that the user of the exercise guidance system 1 uses by wearing it on his / her body (e.g., waist) while running. The smartphone 20 is a portable terminal that the user uses by carrying it while running. The wireless earphone 30 is an ear device that the user uses, like the motion sensor device 10, by wearing it in his / her ear while running. The smartphone 20 is communicably connected by BLE (Bluetooth® Low Energy) with the motion sensor device 10 and the wireless earphone 30.

[0030] Next, a functional configuration of the motion sensor device 10 will be described with reference to FIG. 2. As shown in FIG. 2, the motion sensor device 10 includes a central processing unit (CPU) 11, a random access memory (RAM) 12, a storage 13, a display 14, an operation receiver 15, a sensor unit 16, a sound outputter 17 and a communicator 18. These components of the motion sensor device 10 are connected with one another via a bus 19.

[0031] The CPU 11 controls the components of the motion sensor device 10. The CPU 11 reads a program(s) specified from a system program(s) and application programs stored in the storage 13, loads the read program to the RAM 12, and performs a process among various processes in cooperation with the loaded program. The CPU 11 includes a not-shown timekeeping circuit and obtains the current time measured by the timekeeping circuit. The RAM 12 is a volatile memory and forms a work area where various data and programs are temporarily stored. The storage 13 is composed of, for example, a flash memory, an electrically erasable programmable ROM (EEPROM) or the like. The storage 13 stores the system program and the application programs that are executed by the CPU 11 and data necessary for execution of these programs.

[0032] The display 14 is composed of LED lamps and capable of displaying an ON / OFF state of a power source, a data obtainment state (e.g., whether data is being obtained), a data transmission state (e.g., whether data is being transmitted), an ON / OFF state of a GPS receiver, and so forth. The operation receiver 15 includes a not-shown power button to turn on and off the power source. The CPU 11 controls the components of the motion sensor device 10 on the basis of instructions from this operation receiver 15. The sensor unit 16 includes an acceleration sensor, an angular velocity sensor and the aforementioned GPS receiver and outputs their measurement results to the CPU 11. The sensor unit 16 outputs the measurement results to the CPU 11 at predetermined intervals (e.g., every second, every step of the user, etc.). The measurement results include indicator values (form indicator values) pertaining to form indicators (“Backward Tilt of Trunk”, “Hip Sinking”, “Amount of Breaking”, . . . , and “Ground Contact Time %”, which are shown in FIG. 4) that are learned in (subjects of) lessons, for example, to improve the running form, which will be described later. Alternatively, the CPU 11 may obtain (calculate) form indicator values using data obtained from the sensor unit 16, the data including values of acceleration in directions of three axes as detection results by the acceleration sensor, values of angular velocity in the directions of the three axes as detection results by the angular velocity sensor, and information on the current position (latitude, longitude, altitude, etc.) as detection results by the GPS receiver. The sensor unit 16 may include other sensors in addition to the aforementioned sensors. The sound outputter 17 includes a D / A converter, an amplifier and a speaker. When outputting sound (e.g., voice), the sound outputter 17 converts sound data (e.g., voice data) into analog sound data and outputs the analog sound data through the speaker. The communicator 18 is, for example, a communicator employing a wireless standard, such as Bluetooth, or a wired communicator, such as a USB terminal.

[0033] Next, a functional configuration of the smartphone 20 will be described with reference to FIG. 3. As shown in FIG. 3, the smartphone 20 includes a CPU 21, a RAM 22, a storage 23, a display 24, an operation receiver 25, a sound outputter 26 and a communicator 27. These components of the smartphone 20 are connected with one another via a bus 28.

[0034] The CPU 21 is a processor that reads and executes programs 231 stored in the storage 23 and performs various types of arithmetic processing, thereby controlling the operation of each component of the smartphone 20. Although FIG. 3 shows one CPU 21, the number of CPUs is not limited thereto. Two or more processors, such as CPUs, may be provided, and a plurality of processes that is performed by the CPU 21 in this embodiment may be divided among the two or more processors. The RAM 22 provides a working memory space for the CPU 21 and stores temporary data. The storage 23 stores various data, such as a guidance content database 233 and a running database 234 as well as the programs 231 and a running application 232 that are executed by the CPU 21.

[0035] The programs 231 are stored in the storage 23 in the form of computer-readable program code. The running application 232 is an application for recording running data, such as running track, running distance, running time, pace, pitch and the aforementioned form indicator values, while the user is running. These running data are successively obtained from the motion sensor device 10 while the user is running. The running application 232 has a running guidance function (running form guidance mode) that gives the user who is running guidance on his / her running (exercise) (guidance to improve the running form). In the running database 234, the user's running data recorded during his / her running using the running application 232 is stored.

[0036] In the guidance content database 233, guidance contents that are used in the aforementioned running guidance function (running form guidance mode) are stored. More specifically, as shown in FIG. 4, in the guidance content database 233, guidance contents corresponding to 15 types of lesson (lesson IDs of “001” to “015”) that the user can take in the running guidance function are stored. In the guidance content database 233, reference values for indicator values (form indicator values) pertaining to the form indicators, which are subjects of lessons, are set.

[0037] As shown in FIG. 12, each lesson is composed of four parts; a check part, a learning part, a drill part and a test part (including a first test part and a second test part). In each guidance content in the guidance content database 233, a content for the check part, a content for the learning part, a content for the drill part and a content for the test part are stored. The check part is a part in which the CPU 21 grasps the current state of the running form of the user. More specifically, in the check part, the user is asked to run, and on the basis of a form indicator value measured by the motion sensor device 10 during this running, the current state of the running form of the user is grasped. Then, in a result feedback period following the check part, the current state of the running form of the user is fed back to the user.

[0038] The learning part is a part that comes after the check part and in which the user learns the running form on the basis of the current state of his / her running form. More specifically, in the learning part, a voice (guidance content or first guidance content) for the user to learn the running form is output. In the learning part, as in the check part, the user is asked to run, and a form indicator value measured by the motion sensor device 10 during this running is obtained. Then, in a result feedback period following the learning part, the improvement rate of the form indicator value, the achievement rate based on a target value, and so forth are fed back to the user.

[0039] The drill part is a part that comes after the learning part, i.e., after the user learns (understands in his / her head) the running form, and in which the user actually moves his / her body and understands the running form. More specifically, in the drill part, a voice (guidance content or first guidance content) for the user to understand how to move his / her body, for example, with a slightly exaggerated movement is output. In the drill part, as in the check part and the learning part, the user is asked to run, and a form indicator value measured by the motion sensor device 10 during this running is obtained. Then, in a result feedback period following the drill part, the improvement rate of the form indicator value, the achievement rate based on the target value, and so forth are fed back to the user.

[0040] The test part is a part that comes after the drill part, i.e., after the user understands how to move his / her body, and in which the user runs and the CPU 21 evaluates how well the user can run. More specifically, in the test part, a voice (guidance content or first guidance content) for the user to review what he / she has learned in the learning part and the drill part is output. In the test part, as in the check part, the learning part and the drill part, the user is asked to run, and a form indicator value measured by the motion sensor device 10 during this running is obtained. Then, in an interim feedback period provided in the middle of the test part and a result feedback period following the test part, the improvement rate of the form indicator value, the achievement rate based on the target value, and so forth are fed back to the user.

[0041] Hereinafter, the guidance content database 233 will be further described. Each guidance content stored in the guidance content database 233 and corresponding to each lesson ID is composed of 30 guidance contents corresponding to combinations of six knowledge levels (described later) and five condition levels (described later). For example, as shown in FIG. 5, the guidance content of “Lesson to Improve “Landing Impact”” corresponding to the lesson ID of “007” is broadly divided into six types of guidance content; the guidance content of “Lesson to Learn Basics of “Landing Impact”” for the knowledge level of “0”, the guidance content of “Lesson 2 to Learn Basics of “Landing Impact”” for the knowledge level of “1”, the guidance content of “Lesson Focusing on “Landing Impact” Drill” for the knowledge level of “2”, the guidance content of “Lesson 2 Focusing on “Landing Impact” Drill” for the knowledge level of “3”, the guidance content of “Review Lesson on “Landing Impact”” for the knowledge level of “4”, and the guidance content of “Review Lesson 2 on “Landing Impact”” for the knowledge level of “5”.

[0042] The guidance content of “Lesson to Learn Basics of “Landing Impact”” for the knowledge level of “0” is designed for users who have no knowledge about “Landing Impact” at all. The guidance content of “Lesson 2 to Learn Basics of “Landing Impact”” for the knowledge level of “1” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” but do not understand enough. The guidance content of “Lesson Focusing on “Landing Impact” Drill” for the knowledge level of “2” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” but have some points that they do not understand. The guidance content of “Lesson 2 Focusing on “Landing Impact” Drill” for the knowledge level of “3” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” but have not been able to reflect the lesson in their movement (running form). The guidance content of “Review Lesson on “Landing Impact”” for the knowledge level of “4” is designed for users who have not taken a lesson (guidance) on “Landing Impact” but can perform correct movement. The guidance content of “Review Lesson 2 on “Landing Impact”” for the knowledge level of “5” is designed for users who have taken a lesson(s) (guidance) on “Landing Impact” and can perform correct movement. In other words, each of the 30 guidance contents stored in the guidance content database 233 is a lesson to improve a form indicator (e.g., landing impact) in which user's body movement (form) in running is evaluated, and has a content(s) suitable for the user's knowledge level about the form indicator. More specifically, guidance contents for the knowledge level of “0” are guidance contents for the novice (starter) level, guidance contents for the knowledge level of “1” are guidance contents for the beginner level, guidance contents for the knowledge level of “2” are guidance contents for the beginner-to-intermediate level, guidance contents for the knowledge level of “3” are guidance contents for the intermediate level, guidance contents for the knowledge level of “4” are guidance contents for the intermediate-to-advanced level, and guidance contents for the knowledge level of “5” are guidance contents for the advanced level. In other words, the higher the knowledge level, the higher the level of guidance content.

[0043] Each of the six types of guidance content described above is divided into five types of guidance content for condition levels of “Very Good”, “Good”, “Neither Good Nor Bad”, “Bad” and “Very Bad”. For example, as shown in FIG. 5, the guidance content of “Lesson to Learn Basics of “Landing Impact”” for the knowledge level of “0” is divided into the guidance content of “Lesson to Learn Basics of “Landing Impact” Very Hard” for the condition level of “Very Good”, the guidance content of “Lesson to Learn Basics of “Landing Impact”_Hard” for the condition level of “Good”, the guidance content of “Lesson to Learn Basics of “Landing Impact” Normal” for the condition level of “Neither Good Nor Bad”, the guidance content of “Lesson to Learn Basics of “Landing Impact”_Easy” for the condition level of “Bad”, and the guidance content of “Lesson to Learn Basics of “Landing Impact”_Very Easy” for the condition level of “Very Bad”. As shown in FIG. 12, each guidance content is composed of multiple voice files that are provided (output) in a check part period Va, a result feedback period Vb on the check part, a learning part period Vc, a result feedback period Vd on the learning part, a drill part period Ve, a result feedback period Vf on the drill part, a first test part period Vg, an interim feedback period Vh, a second test part period Vi, and a result feedback period Vj on the test part.

[0044] Returning to FIG. 3, the display 24 is composed of a liquid crystal display (LCD) or the like, and displays screens in accordance with display control signals from the CPU 21. On the display screen of the display 24, touch sensors are disposed, so that the display 24 functions as a touchscreen operation-and-display means. The operation receiver 25 includes pushbutton switches and the aforementioned touch sensors disposed on the display 24, and receives user's input operations, converts the contents of the operations into electric signals, and outputs the electric signals to the CPU 21. The sound outputter 26 includes a D / A converter, an amplifier and a speaker. When outputting sound (e.g., voice), the sound outputter 26 converts sound data (e.g., voice data) into analog sound data and outputs the analog sound data through the speaker. The communicator 27 is, for example, a communicator employing a wireless standard, such as Bluetooth, or a wired communicator, such as a USB terminal. The communicator 27 performs wireless data communication with the communicator 18 of the motion sensor device 10 and a communicator 37 of the wireless earphone 30 described below, for example.

[0045] Next, a functional configuration of the wireless earphone 30 will be described with reference to FIG. 6. As shown in FIG. 6, the wireless earphone 30 includes a CPU 31, a RAM 32, a storage 33, a display 34, an operation receiver 35, a sound outputter 36 and the aforementioned communicator 37. These components of the wireless earphone 30 are connected with one another via a bus 38.

[0046] The CPU 31 controls the components of the wireless earphone 30. The CPU 31 reads a program(s) specified from a system program(s) and application programs stored in the storage 33, loads the read program to the RAM 32, and performs a process among various processes in cooperation with the loaded program. The RAM 32 is a volatile memory and forms a work area where various data and programs are temporarily stored. The storage 33 is composed of, for example, a flash memory, an EEPROM or the like. The storage 33 stores the system program and the application programs that are executed by the CPU 31 and data necessary for execution of these programs.

[0047] The display 34 is composed of LED lamps and capable of displaying an ON / OFF state of a power source, the remaining life of a battery, and so forth. The operation receiver 35 includes a not-shown power button to turn on and off the power source and a not-shown adjustment button to adjust the level of sound that is output from the sound outputter 36. The CPU 31 controls the components of the wireless earphone 30 on the basis of instructions from this operation receiver 35. The sound outputter 36 includes a D / A converter, an amplifier and a speaker. When outputting sound (e.g., voice), the sound outputter 36 converts sound data (e.g., voice data) into analog sound data and outputs the analog sound data through the speaker. The communicator 37 is, for example, a communicator employing a wireless standard, such as Bluetooth.

[0048] Next, the operation of the exercise guidance system 1 will be described. More specifically, a running form guidance process that is performed by the CPU 21 of the smartphone 20 will be described. This running form guidance process is performed, for example, when the running form guidance mode (running guidance function) is selected from among multiple modes while the running application 232 is running.

[0049] As shown in FIG. 7, when the running form guidance process is started, first, the CPU 21 of the smartphone 20 causes the display 24 to display a lesson selection screen G1 (Step S1). As shown in FIG. 8, in the lesson selection screen G1, message information (e.g., “Select Lesson to Take”) G11 that urges the user to select a lesson to take is displayed at the top of the screen. The lesson selection screen G1 is provided with selection buttons G12 under the message information G11. The selection buttons G12 correspond to selectable lessons. The screen example shown in FIG. 8 shows a state in which a selection button G12 corresponding to “Lesson to Improve “Landing Impact”” is operated. The lesson selection screen G1 is also provided with an enter button G13 and a stop button G14 at the bottom of the screen. The enter button G13 is used for fixing, as the lesson to take (which hereinafter may be referred to as “target lesson”), the lesson selected (e.g., “Lesson to Improve “Landing Impact””) by the selection button (G12) being selected. The stop button G14 is used for stopping the running form guidance mode. When the stop button G14 is operated, the display 24 displays a not-shown home screen of the running application 232.

[0050] Returning to FIG. 7, after performing the process of Step S1, the CPU 21 determines whether the stop button G14 has been operated (Step S2). If the CPU 21 determines in Step S2 that the stop button G14 has been operated (Step S2; YES), the CPU 21 ends the running form guidance process. If the CPU 21 determines in Step S2 that the stop button G14 has not been operated (Step S2; NO), the CPU 21 determines whether operations to select and fix a lesson have been made (Step S3). The operations to select and fix a lesson mean operating one of the selection buttons G12 and then operating the enter button G13. As described above, the buttons G12, G13 are disposed on the lesson selection screen G1.

[0051] If the CPU 21 determines in Step S3 that the operations to select and fix a lesson have not been made (Step S3; NO), the CPU 21 returns to Step S2 and repeats the processes of Step S2 and the subsequent step(s). If the CPU 21 determines in Step S3 that the operations to select and fix a lesson have been made (Step S3; YES), the CPU 21 instructs the user to start running (Step S4). More specifically, the CPU 21 transmits voice data for instructing the user to start running to the wireless earphone 30 via the communicator 27, and causes the sound outputter 36 of the wireless earphone 30 to output a voice based on the voice data (e.g., “In order to grasp current running form, start running”). When the CPU 21 performs the process of Step S4, the motion sensor device 10 is already ready to derive / measure data (running data) such as form indicator values mentioned above. By the CPU 21 performing the process of Step S4, the check part (shown in FIG. 12) of the lesson (e.g., “Lesson to Improve “Landing Impact””) that the user takes starts.

[0052] Next, the CPU 21 determines whether a predetermined time (e.g., five minutes) has elapsed from the completion of the process of Step S4 (Step S5). If the CPU 21 determines in Step S5 that the predetermined time has not elapsed (Step S5; NO), the CPU 21 repeats the process of Step S5 until the predetermined time elapses. If the CPU 21 determines in Step S5 that the predetermined time has elapsed (Step S5; YES), the CPU 21 instructs the user to stop running (Step S6). More specifically, the CPU 21 transmits voice data for instructing the user to stop running to the wireless earphone 30 via the communicator 27, and causes the sound outputter 36 of the wireless earphone 30 to output a voice (e.g., “Stop running”) based on the voice data. By the CPU 21 performing the process of Step S6, the check part (shown in FIG. 12) of the lesson (e.g., “Lesson to Improve “Landing Impact””) that the user is taking finishes. The period from when the instruction to start running is made (and the user actually starts running) until when the predetermined time elapses is the check part period Va (shown in FIG. 12). In this check part period Va, a voice for (corresponding to) this period Va is output from the sound outputter 36 of the wireless earphone 30. More specifically, as shown in FIG. 13 and FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the check part period Va, a voice of “Today, we will give you a lesson on landing impact. First, we will check your current state, so relax and run for five minutes as usual.” The voice data of this voice corresponds to the content for the check part. In other words, the content is obtained from the guidance content database 233 using the instruction to start running as a trigger.

[0053] Next, the CPU 21 obtains a form indicator value pertaining to the form indicator, which is the subject of the lesson that the user is taking (Step S7). More specifically, the CPU 21 obtains, via the communicator 27, a form indicator value pertaining to the form indicator, which is the subject of the lesson that the user is taking, measured between when the CPU 21 instructs the user to start running in Step S4 and when the CPU 21 instructs the user to stop running in Step S6. If the lesson that the user is taking is “Lesson to Improve “Landing Impact””, the CPU 21 obtains a form indicator value pertaining to the form indicator of “Landing Impact” (shown in FIG. 4) as the subject of the lesson.

[0054] Next, the CPU 21 performs a knowledge level determination process (Step S8). As shown in FIG. 9, when the knowledge level determination process is started, the CPU 21 determines whether the form indicator value obtained in Step S7 of the running form guidance process (shown in FIG. 7) satisfies its reference value (shown in FIG. 4) (Step S21). The form indicator value that is used for this determination is the mean of all form indicator values pertaining to the form indicator measured from the start of running in Step S4 to the end of running in Step S6 but not limited thereto. The form indicator value may be the median, the mode or the like. There are two types of form indicator. One type of form indicator is a form indicator whose form indicator value indicates a better state as it is smaller. Examples thereof include “Backward Tilt of Trunk”, “Hip Sinking”, “Amount of Breaking”, “Vertical Movement” and “Landing Impact”. The other type of form indicator is a form indicator whose form indicator value indicates a better state as it is larger. Examples thereof include “Lifting-up of Pelvis” and “Stiffness”. Therefore, in the case of a form indicator whose form indicator value indicates a better state as it is smaller, the CPU 21 determines that the form indicator value pertaining to the form indicator satisfies its reference value if the form indicator value is equal to or less than the reference value, and determines that the form indicator value does not satisfy the reference value if the form indicator value is greater than the reference value. On the other hand, in the case of a form indicator whose form indicator value indicates a better state as it is larger, the CPU 21 determines that the form indicator value pertaining to the form indicate satisfies its reference value if the form indicator value is equal to or greater than its reference value, and determines that the form indicator value does not satisfy the reference value if the form indicator value is less than the reference value.

[0055] If the CPU 21 determines in Step S21 that the form indicator value does not satisfy the reference value (Step S21; NO), the CPU 21 determines how many times the user has taken this target lesson (Step S22). The number of times the user has taken the target lesson is stored in the running database 234. If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is zero (Step S22; Zero), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “0” (Step S23). If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is one (Step S22; Once), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “1” (Step S24). If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is two (Step S22; Twice), the CPU 21 determines that the knowledge level of the user about the form indicator that is the subject of the target lesson is “2” (Step S25). If the CPU 21 determines in Step S22 that the number of times the user has taken the target lesson is three or more (Step S22; Three times or more), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “3” (Step S26). After performing the process of Step S23, Step S24, Step S25 or Step S26, the CPU 21 returns to the running form guidance process.

[0056] If the CPU 21 determines in Step S21 that the form indicator value satisfies the reference value (Step S21; YES), the CPU 21 determines how many times the user has taken this target lesson (Step S27). If the CPU 21 determines in Step S27 that the number of times the user has taken the target lesson is zero (Step $27; Zero), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “4” (Step S28). If the CPU 21 determines in Step S27 that the number of times the user has taken the target lesson is once or more (Step S27; Once or more), the CPU 21 determines that the knowledge level of the user about the form indicator as the subject of the target lesson is “5” (Step $29). After performing the process of Step S28 or Step S29, the CPU 21 returns to the running form guidance process. In other words, the knowledge level is a value that is set on the basis of the form indicator value pertaining to the form indicator and the number of times the user has taken the target lesson, the subject of which is the form indicator.

[0057] Returning to FIG. 7, after performing the knowledge level determination process, the CPU 21 performs a condition level determination process (Step S9). As shown in FIG. 10, when the condition level determination process is started, the CPU 21 determines whether the user's running records (running data) of the last three times (of running) are stored in the running database 234 (Step S41). If the CPU 21 determines in Step S41 that the running records (running data) of the last three times are not stored in the running database 234 (Step S41; NO), the CPU 21 determines that the condition level of the user is “Neither Good Nor Bad” (Step S50). The CPU 21 then returns to the running form guidance process.

[0058] If the CPU 21 determines in Step S41 that the running records (running data) of the last three times are stored in the running database 234 (Step S41; YES), the CPU 21 derives, on the basis of the running records, the mean (B) of the average paces in a period of beginning of running of the last three times (Step S42). This “period of beginning of running” is, for example, five minutes (equivalent to the period of the check part) from the start of running. Next, the CPU 21 derives the average pace (A) in the period of beginning of running of this time (Step S43). In other words, in Step S43, the CPU 21 derives the average pace (A) of the user's running in the period of the check part (shown in FIG. 12).

[0059] Next, the CPU 21 compares the average pace (A) in the period of beginning of running of this time derived in Step S43 with the mean (B) of the average paces in the period of beginning of running of the last three times derived in Step S42 (Step S44). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is 30 seconds or more faster than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; 30 seconds or more faster), the CPU 21 determines that the condition level of the user is “Very Good” (Step S45). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is more than 10 seconds but less than 30 seconds faster than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; more than 10 seconds but less than 30 seconds faster), the CPU 21 determines that the condition level of the user is “Good” (Step S46). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is ±10 seconds compared to the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; ±10 seconds), the CPU 21 determines that the condition level of the user is “Neither Good Nor Bad” (Step S47). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is more than 10 seconds but less than 30 seconds slower than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; more than 10 seconds but less than 30 seconds slower), the CPU 21 determines that the condition level of the user is “Bad” (Step S48). If the CPU 21 determines in Step S44 that the average pace (A) in the period of beginning of running of this time is 30 seconds or more slower than the mean (B) of the average paces in the period of beginning of running of the last three times (Step S44; 30 seconds or more slower), the CPU 21 determines that the condition level of the user is “Very Bad” (Step S49). After performing the process of Step S45, Step S46, Step S47, Step S48 or Step S49, the CPU 21 returns to the running form guidance process.

[0060] Returning to FIG. 7, after performing the condition level determination process, the CPU 21 obtains a guidance content to be provided to the user in the target lesson (Step S10). For example, if the target lesson is “Lesson to Improve “Landing Impact””, the knowledge level of the user determined in Step S8 is “1”, and the condition level of the user determined in Step S9 is “Good”, the CPU 21 obtains “Lesson 2 to Learn Basics of “Landing Impact”_Hard” from the guidance content database 233 (shown in FIG. 5) as the guidance content to be provided to the user. As another example, if the target lesson is “Lesson to Improve “Landing Impact””, the knowledge level of the user determined in Step S8 is “3”, and the condition level of the user determined in Step S9 is “Bad”, the CPU 21 obtains “Lesson 2 Focusing on “Landing Impact” Drill Easy” from the guidance content database 233 (shown in FIG. 5) as the guidance content to be provided to the user.

[0061] Next, the CPU 21 performs a guidance content provision process on the basis of the guidance content obtained in Step S10 (Step S11). As shown in FIG. 11, when the guidance content provision process is started, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vb on the check part (shown in FIG. 12), a voice for the result feedback period Vb on the basis of the guidance content obtained in Step S10 (Step S61). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vb on the check part, a voice of “You seem in a good condition today. Go for the highest achievement rate ever. Today's reference value is 25.0.” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vb on the check part, a voice of “You seem in a bad condition today. Take it easy and do the best you can today. Today's reference value is 25.0.”

[0062] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the learning part period Vc (shown in FIG. 12), a voice for this period Vc (Step S62). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the learning part period Vc, a voice of “In this lesson, you will run while learning the basics of landing impact again. There are three main causes of high landing impact. The first one is landing on the heel, the second one is not shifting the weight properly and putting the brakes on yourself, and the third one is . . . . Run for a while, keeping in mind what you have learned . . . .” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the learning part period Vc, a voice of “In this lesson, you will run while learning landing impact in more depth. You will learn a technique for shifting the weight from stable landing. We will first explain how to swing down below the knees . . . . Run for a while, keeping in mind what you have learned . . . .”

[0063] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vd on the learning part (shown in FIG. 12), a voice for this period Vd (Step S63). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vd on the learning part, a voice of “You showed 7% improvement. Go for more improvement today.” The “7% improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the learning part period Vc. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vd on the learning part, a voice of “You showed no improvement. Take it easy and run comfortably today. It is important to run with awareness even if you cannot get a result.” The “no improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the learning part period Vc.

[0064] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the drill part period Ve (shown in FIG. 12), a voice for this period Ve (Step S64). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the drill part period Ve, a voice of “In this drill, you will try the basic drill again. First, for learning posture, move to a safe place where you can stop . . . . Run for a while, keeping in mind the feelings you had during the drill . . . ” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the drill part period Ve, a voice of “In this drill, you will try a technical drill. First, for learning steps, move to a safe place where you can get a straight line of about 20 m . . . . Run for a while, keeping in mind the feelings you had during the drill . . . .”

[0065] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vf on the drill part (shown in FIG. 12), a voice for this period Vf (Step S65). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vf on the drill part, a voice of “You showed 10% improvement. Go for more improvement today.” The “10% improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the drill part period Ve. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vf on the drill part, a voice of “You showed 5% improvement. Take it easy and run slowly with awareness today.” The “5% improvement” output by the voice is information derived on the basis of the form indicator values pertaining to “Landing Impact” measured in the check part period Va and the drill part period Ve.

[0066] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the first test part period Vg (shown in FIG. 12), a voice for this period Vg (Step S66). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the first test part period Vg, a voice of “From here on, run for an achievement rate of 90%, keeping in mind what you have learned today. So, start. First of all, it is important to keep straightening your back up . . . .” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the first test part period Vg, a voice of “From here on, run for an achievement rate of 80%, keeping in mind what you have learned today. So, start. First of all, lifting your legs up is . . . .”

[0067] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the interim feedback period Vh (shown in FIG. 12), a voice for this period Vh (Step S67). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the interim feedback period Vh, a voice of “The achievement rate so far is 78%. Focus on the posture and land softly on the middle of the foot.” The “achievement rate so far is 78%” is information derived on the basis of the form indicator value pertaining to “Landing Impact” measured in the first test part period Vg and the reference value for “Landing Impact”. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the interim feedback period Vh, a voice of “The achievement rate so far is 65%. Focus on the speed at which you return your feet to match the road speed, but don't push yourself hard.” The “achievement rate so far is 65%” is information derived on the basis of the form indicator value pertaining to “Landing Impact” measured in the first test part period Vg and the reference value for “Landing Impact”.

[0068] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the second test part period Vi (shown in FIG. 12), a voice for this period Vi (Step S68). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the second test part period Vi, a voice of “Run one more time for an achievement rate of 90%, keeping in mind what you have learned today. So, start. First of all, it is important to keep straightening your back up.” As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the second test part period Vi, a voice of “Run one more time for an achievement rate of 80%, keeping in mind what you have learned today. So, start. First of all, lifting your legs up is . . . .”

[0069] Next, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vj on the test part (shown in FIG. 12), a voice for this period Vj (Step S69). For example, if the guidance content obtained in Step S10 is “Lesson 2 to Learn Basics of “Landing Impact”_Hard”, as shown in FIG. 13, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vj on the test part, a voice of “It's time for a cool-down. Walk and get your breathing under control . . . . Let's take a look at today's results. The achievement rate is 88% with respect to the reference value of 25.0. You did not reach the goal today. Keep trying to achieve the goal.” The “achievement rate is 88%” output by the voice is information derived on the basis of the form indicator value(s) pertaining to “Landing Impact” measured in the periods from the first test part period Vg to the interim feedback period Vh or from the first test part period Vg through the interim feedback period Vh to the second test part period Vi and the reference value for “Landing Impact”. As another example, if the guidance content obtained in Step S10 is “Lesson 2 Focusing on “Landing Impact” Drill_Easy”, as shown in FIG. 14, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output, in the result feedback period Vj on the test part, a voice of “It's time for a cool-down. Walk and get your breathing under control . . . . Let's take a look at today's results. The achievement rate is 69% with respect to the reference value of 25.0. You did not reach the goal today. Take it easy and make steady improvement.” The “achievement rate is 69%” is information derived on the basis of the form indicator value(s) pertaining to “Landing Impact” measured from the first test part period Vg to the interim feedback period Vh or from the first test part period Vg through the interim feedback period Vh to the second test part period Vi and the reference value for “Landing Impact”. After performing the process of Step S69, the CPU 21 returns to the running form guidance process. The CPU 21 then ends the running form guidance process.

[0070] As shown in FIG. 11 and FIG. 12, the CPU 21 performs the process in the first test part period Vg, the process in the interim feedback period Vh, the process in the second test part period Vi and the process in the result feedback period Vj in this order, but the present disclosure is not limited thereto. For example, after performing the process in the first test part period Vg, the CPU 21 may perform the process in the result feedback period Vj without performing the process in the second test part period Vi. In this case, the CPU 21 may perform the process in the second test part period Vi if an indicator value measured in the first test part period Vg satisfies a predetermined condition, and not perform the process in the second test part period Vi if the indicator value measured in the first test part period Vg does not satisfy the predetermined condition. To be more specific, a not-shown condition determination step may be added between Step S66 and Step S67. Examples of the predetermined condition include a condition that an indicator value (heart rate) measured by a heart rate sensor included in the sensor unit 16 is equal to or less than a predetermined value, and a condition that a form indicator value pertaining to a predetermined form indicator (“Landing Impact” in this embodiment) among the form indicators is equal to or less than a predetermined value (or equal to or greater than a predetermined value depending on the type of form indicator). If the CPU 21 determines to skip the second test part period Vi on the basis of the indicator value measured in the first test part period Vg, the CPU 21 may skip the interim feedback period Vh too. That is, after performing the process in the first test part period Vg, the CPU 21 may perform the process in the result feedback period Vj. Thus, if the CPU 21 determines, from the measured indicator value, that the user seems to still have enough strength, the CPU 21 takes the second test part period Vi next to the interim feedback period Vh, thereby being able to provide, to the user, information beneficial for the user efficiently. In the same manner, after the second test part period Vi, a not-shown third test part period may be provided on the basis of the indicator value measured in the second test part period Vi. If the third test part period is provided, a not-shown interim feedback period, which is similar to the interim feedback period Vh, may also be provided between the second test part period Vi and the third test part period.

[0071] The conventional running form determination device disclosed in JP H2-203842 A determines whether the running form is good numerically, and therefore has a problem that the determination result is difficult to understand. Thus, this running form determination device cannot make use of the determination result or improve the running form efficiently.

[0072] In contrast, the CPU 21 of the smartphone 20 of this embodiment selects (obtains) a content guidance pertaining to a predetermined form indicator from among guidance contents about movement of the body of a user in running (exercise). Further, the CPU 21 obtains a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is running (doing the exercise). Further, the CPU 21 provides the selected guidance content to the user who is running, by performing, with respect to each guidance timing of guidance timings (check part, learning part, drill part and test part) during running, a series of processes of providing a first guidance content (e.g., content for the check part, i.e., voice for the check part period Va) corresponding to each guidance timing and providing a second guidance content (e.g., content that is provided in the result feedback period Vb, i.e., voice for the result feedback period Vb) corresponding to the result of the form indicator value that the CPU 21 obtains while providing the first guidance content, in the order named. Thus, with respect to each guidance timing, the smartphone 20 provides the first guidance content to the user, thereby giving the user a lesson (guidance) on the movement of the body of the user in running, and provides the second guidance content to the user, thereby feeding back, to the user, the result of the user moving his / her body under the guidance, and therefore can improve the running form efficiently.

[0073] Further, the CPU 21 of the smartphone 20 provides the first guidance content and the second guidance content, the first guidance content corresponding to each guidance timing of the guidance timings of the check part in which the CPU 21 grasps the current state of the movement of the body of the user, the learning part that comes after the check part and in which the user learns how to move the body of the user based on the current state of the movement of the body of the user, the drill part that comes after the learning part and in which the user actually moves the body and understands how to move the body, and the test part that comes after the drill part and in which the user runs and the CPU 21 evaluates the movement of the body of the user in the running (exercise). Thus, the smartphone 20 gives the user guidance in four parts; the check part, the learning part, the drill part and the test part, and therefore can improve the running form even more efficiently.

[0074] Further, the CPU 21 of the smartphone 20 obtains the form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is running (doing the exercise) and derived based on measured data obtained by the motion sensor device 10 (motion sensor) worn on the body of the user performing sampling. Thus, the smartphone 20 can obtain an accurate form indicator value, and therefore can give the user appropriate feedback in providing the second guidance content.

[0075] Further, the test part is provided with at least one interim feedback period (Vh) (shown in FIG. 12) in which interim feedback included in the first guidance content is given to the user, before a result feedback period (Vj) (shown in FIG. 12) in which result feedback included in the second guidance content is given to the user. Therefore, the smartphone 20 allows the user to check, in the interim feedback period Vh, how his / her running form has been changed and to easily adjust the running form.

[0076] Further, the CPU 21 of the smartphone 20 determines the knowledge level of the user about running (exercise), and based on the determined knowledge level, selects (obtains) the guidance content for the knowledge level. Thus, in providing the guidance content, the smartphone 20 provides the guidance content for the knowledge level of the user about running, and therefore can provide, to the user, the guidance content beneficial to the user.

[0077] Next, a modification of the running form guidance process (shown in FIG. 7) will be described. The running form guidance process according to this modification is characterized in that the CPU 21 determines a form indicator to be improved from form indicator values pertaining to form indicators measured in the check part, and provides, to the user, a guidance content corresponding to the determined form indicator.

[0078] As shown in FIG. 15, when the running form guidance process according to the modification is started, first, the CPU 21 of the smartphone 20 instructs the user to start running (Step S101). More specifically, the CPU 21 transmits voice data for instructing the user to start running to the wireless earphone 30 via the communicator 27. The CPU 21 then causes the sound outputter 36 of the wireless earphone 30 to output a voice (e.g., “In order to determine a form indicator to be improved, start running.”) based on the voice data. When the CPU 21 performs the process of Step S101, the motion sensor device 10 is already ready to derive / measure data (running data) such as form indicator values mentioned above. By the CPU 21 performing the process of Step S101, the check part Va (shown in FIG. 12) of the lesson (running form guidance) that the user takes starts.

[0079] Next, the CPU 21 determines whether a predetermined time (e.g., five minutes) has elapsed from the completion of the process of Step S101 (Step S102). If the CPU 21 determines in Step S102 that the predetermined time has not elapsed (Step S102; NO), the CPU 21 repeats the process of Step S102 until the predetermined time elapses. If the CPU 21 determines in Step S102 that the predetermined time has elapsed (Step S102; YES), the CPU 21 instructs the user to stop running (Step S103). More specifically, the CPU 21 transmits voice data for instructing the user to stop running to the wireless earphone 30 via the communicator 27, and causes the sound outputter 36 of the wireless earphone 30 to output a voice (e.g., “Stop running”) based on the voice data. By the CPU 21 performing the process of Step S103, the check part Va (shown in FIG. 12) of the lesson (running form guidance) that the user is taking finishes.

[0080] Next, the CPU 21 performs an improvement-required form indicator determination process (Step S104). As shown in FIG. 16, when the improvement-required form indicator determination process is started, the CPU 21 sets the value of a variable “X” to the initial value of “1”, and obtains a form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first (highest) priority (Priority_1) (X=1) (shown in FIG. 17) (Step S121). Next, the CPU 21 determines whether the form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) obtained in Step S121 satisfies its reference value of “1.0” (Step S122). As to a form indicator value pertaining to a certain form indicator, if the form indicator value is equal to or less than its reference value, it is determined that the exercise form is proper in terms of the form indicator and accordingly it is determined that the form indicator value satisfies the reference value. As to a form indicator value of another certain form indicator, if the form indicator value is equal to or greater than its reference value, it is determined that the exercise form is proper in terms of the form indicator and accordingly it is determined that the form indicator value satisfies the reference value. As a specific example, in the case of a form indicator value pertaining to “Backward Tilt of Trunk”, it is determined that the form indicator value satisfies its reference value if the form indicator value is equal to or less than “1.0”, which is the reference value for “Backward Tilt of Trunk”. As another specific example, in the case of a form indicator value pertaining to “Kickout Acceleration”, it is determined that the form indicator value satisfies its reference value if the form indicator value is equal to or greater than “45”, which is the reference value for “Kickout Acceleration”.

[0081] If the CPU 21 determines in Step S122 that the form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) does not satisfy its reference value of “1.0” (Step S122; NO), the CPU 21 determines the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) as the form indicator to be improved (Step S125). That is, in this case, the check part and the subsequent parts of the lesson are conducted with the form indicator of “Backward Tilt of Trunk” as the form indicator to be improved.

[0082] If the CPU 21 determines in Step S122 that the form indicator value pertaining to the form indicator of “Backward Tilt of Trunk” having the first priority (Priority_1) satisfies its reference value of “1.0” (Step S122; YES), the CPU 21 increases the value of “X” in “Priority X” by one, and obtains a form indicator value pertaining to the form indicator of “Hip Sinking” having the second priority (Priority_2) (shown in FIG. 17) (Step S123). The CPU 21 determines whether the value of “X” increased by one in Step S123 is 16 (Step S124).

[0083] If the CPU 21 determines in Step S124 that the value of “X” increased by one in Step S123 is not 16 (Step S124; NO), the CPU 21 returns to Step $122 and repeats the processes of Step S122 and the subsequent steps. For example, if the CPU 21 determines in Step S122 that the form indicator value pertaining to the form indicator of “Landing Impact” having the seventh priority (Priority_7) does not satisfy its reference value of “25.0” (Step S122; NO), the CPU 21 determines the form indicator of “Landing Impact” having the seventh priority (Priority_7) as the form indicator to be improved (Step S125). That is, in this case, the check part and the subsequent parts of the lesson are conducted with the form indicator of “Landing Impact” as the form indicator to be improved.

[0084] If the CPU 21 determines in Step S124 that the value of “X” increased by one in Step S123 is 16 (Step S124; YES), namely, determines that the form indicator values pertaining to the form indicators having the first priority (Priority_1) to the 15th priority (Priority_15) all satisfy their respective reference values, the CPU 21 ends the improvement-required form indicator determination process without determining the form indicator to be improved, and returns to the running form guidance process (shown in FIG. 15).

[0085] Returning to FIG. 15, the CPU 21 determines whether the form indicator to be improved has been determined in the improvement-required form indicator determination process (Step S105). If the CPU 21 determines in Step S105 that the form indicator to be improved has been determined (Step S105; YES), the CPU 21 performs the knowledge level determination process (Step S106), the condition level determination process (Step S107), the process of obtaining a guidance content to be provided to the user (Step S108) and the guidance content provision process (Step S109), and then ends the running form guidance process. Since the processes of Step S106 to Step S109 are the same as the processes of Step S8 to Step S11 described with reference to FIG. 7, respectively, their detailed descriptions will be omitted.

[0086] If the CPU 21 determines in Step S105 that the form indicator to be improved has not been determined (Step S105; NO), namely, determines that the form indicator values pertaining to the form indicators having the first priority (Priority_1) to the 15th priority (Priority_15) all satisfy their respective reference values, the CPU 21 notifies the user of the end of the running form guidance (Step S110). More specifically, the CPU 21 causes the sound outputter 36 of the wireless earphone 30 to output a voice indicating the end of the running form guidance (e.g., “Since the form indicator to be improved is not present, the running form guidance will be ended”). The CPU 21 then ends the running form guidance process. Although in the above, if the CPU 21 determines in Step S105 that the form indicator to be improved has not been determined (Step S105; NO), the CPU 21 ends the running form guidance, the present disclosure is not limited thereto. For example, if the CPU 21 determines in Step S105 that the form indicator to be improved has not been determined (Step S105; NO), the CPU 21 may refer to form indicator values (e.g., form indicator values pertaining to the 15 types of form indicator shown in FIG. 17) in user's previous (e.g., last) running that are recorded / stored in the running database 234, compare these with their respective reference values, and determine, as the form indicator to be improved, a form indicator whose form indicator value is farthest from its reference value. In this case, on the basis of the form indicator thus determined, the CPU 21 performs the processes of Steps S106 to S109 shown in FIG. 15.

[0087] Those described in the above embodiment are not limitations but mere examples of the exercise guidance device, the exercise guidance method and the program stored in the storage medium according to the present disclosure. For example, although in the above embodiment, the contents of a guidance content (e.g., “Lesson 2 to Learn Basics of “Landing Impact”_Hard”) that is provided in a lesson is determined on the basis of the knowledge level and the condition level of the user, this determination method is a mere example. For example, the contents of a guidance content that is provided in a lesson may be determined in accordance with the state of a form indicator value(s) pertaining to a form indicator(s) other than the form indicator that is the subject of the lesson. For example, a form indicator value pertaining to “Landing Impact” not satisfying its reference value may be partly due to a form indicator value pertaining to “Backward Tilt of Trunk” and / or a form indicator value pertaining to “Hip Sinking” not satisfying its / their reference value(s). Therefore, for example, if the form indicator as the subject of the lesson is “Landing Impact”, and the form indicator value pertaining to “Backward Tilt of Trunk” and the form indicator value pertaining to “Hip Sinking” do not satisfy their respective reference values, the guidance content having the contents that refer to these form indicators too may be determined as the guidance content that is provided in the lesson. On the other hand, if the form indicator value pertaining to “Backward Tilt of Trunk” and the form indicator value pertaining to “Hip Sinking” satisfy their respective reference values, the guidance content having the contents that do not refer to these form indicators may be determined as the guidance content that is provided in the lesson. The relationship between the form indicator of “Landing Impact” whose indicator value does not satisfy its reference value and another form indicator(s) (e.g., “Backward Tilt of Trunk”, “Hip Sinking”, etc.) that could be the cause may be stored in advance in a not-shown database in the storage 23.

[0088] Further, although in the above embodiment, when providing the guidance content in the guidance content provision process (Step S11) of the running form guidance process (shown in FIG. 7) and mentioning the advancement rate of the form indicator value of the subject of the lesson as shown in FIG. 13 and FIG. 14, the CPU 21 derives the achievement rate using the reference value (default reference value) set in the guidance content database 233 (shown in FIG. 4), this reference value may be changeable. More specifically, if the mean (which hereinafter may be referred to as “target indicator mean”) of the form indicator values pertaining to the form indicator as the subject of the lesson in the period of beginning of running of the last three times does not satisfy the default reference value, the CPU 21 sets the reference value that is used for deriving the achievement rate to the default reference value. On the other hand, if the mean of the form indicator values pertaining to the form indicator as the subject of the lesson in the period of beginning of running of the last three times satisfies the default reference value, the CPU 21 sets the reference value that is used for deriving the achievement rate to a reference value calculated by Formula (1) or Formula (2) below.<For Form Indicator Whose Form Indicator Value Indicates Better State as it is Larger>Reference⁢ Value=Target⁢ Indicator⁢ Mean+(Target⁢ Indicator⁢ Mean×Intensity⁢ Coefficient×Condition⁢ Coefficient)Formula⁢ (1)<For Form Indicator Whose Form Indicator Value Indicates Better State as it is Smaller>Reference⁢ Value=Target⁢ Indicator⁢ Mean-(Target⁢ Indicator⁢ Mean×Intensity⁢ Coefficient×Condition⁢ Coefficient)Formula⁢ (2)The “Intensity Coefficient” is set for user's desired intensity that is set on the basis of a user operation. If the user desires “Hard”, the intensity coefficient is set to “0.6”. If the user desires “Normal”, the intensity coefficient is set to “0.3”. If the user desires “Easy”, the intensity coefficient is set to “0.1”. As the “Condition Coefficient”, a coefficient for the condition level determined in the condition level determination process (shown in FIG. 10) is set. If the condition level determined in the condition level determination process is “Very Good”, a condition coefficient of “1.2” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “0.7” is set. If the determined condition level is “Good”, a condition coefficient of “1.1” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “0.8” is set. If the determined condition level is “Neither Good Nor Bad”, a condition coefficient of “1.0” is set. If the determined condition level is “Bad”, a condition coefficient of “0.8” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “1.1” is set. If the determined condition level is “Very Bad”, a condition coefficient of “0.7” is set. However, in the case of a form indicator having an inverse correlation with the running pace, a condition coefficient of “1.2” is set.

[0090] There are two types of form indicator as subjects of lessons; form indicators whose form indicator values are likely to fluctuate and form indicators whose form indicator values are unlikely to fluctuate. Therefore, in the case where the reference value is changeable as described above, the reference value may be calculated in accordance with the form indicator as the subject of the lesson by using a calculation formula suitable for the form indicator.

[0091] Further, although in the above embodiment, the guidance content obtained in Step S10 of the running form guidance process (shown in FIG. 7) is provided in each period thereafter, i.e., from the result feedback period Vb on the check part, the type of guidance content to be provided may be changed, for example, part by part. More specifically, in the learning part period Vc, a form indicator value pertaining to a form indicator as the subject of a lesson is measured, and if the form indicator value measured in the learning part period Vc shows 5% or more improvement compared to the form indicator value measured in the check part period Va, the knowledge level is raised by two levels (e.g., if the current knowledge level is “1”, it is raised to “3”). As another example, if the form indicator value measured in the learning part period Vc shows more than 0% but less than 5% improvement compared to the form indicator value measured in the check part period Va, the current knowledge level is raised by one level. As another example, if the form indicator value measured in the learning part period Vc shows no (0% or less) improvement compared to the form indicator value measured in the check part period Va, the current knowledge level maintains the status quo. In the case where there is a change in the knowledge level, the guidance content to be provided to the user is reobtained on the basis of the knowledge level after the change and the condition level determined in the condition level determination process (Step S9). Then, the obtained guidance content is provided to the user in the result feedback period Vd on the learning part and in the drill part period Ve. The same process may be performed in the drill part period Ve, and if there is a change in the knowledge level, the guidance content to be provided to the user is reobtained on the basis of the knowledge level after the change and the condition level determined in the condition level determination process (Step S9). Then, the obtained guidance content is provided to the user in each period thereafter, i.e., from the result feedback period Vf on the drill part.

[0092] Further, although in the running form guidance process (shown in FIG. 7) of the above embodiment, the guidance content for the knowledge level and the condition level of the user is obtained from the guidance content database 233, the guidance content to be provided to the user may be generated, for example, by inputting the knowledge level, the condition level and the running data of the user into a predetermined machine-learned model. This machine-learned model is a model machine-learned with training data (training information) in each of which data of the knowledge level and the condition level of a user both determined in the check part of a lesson, the contents of a guidance content provided to the user in each part (learning part, drill part, test part) of the lesson and running data of the user in each part of the lesson are associated with, as a correct answer, the achievement rate of the form indicator value pertaining to the form indicator as the subject of the lesson with respect to its reference value.

[0093] Further, although in the above embodiment, result feedback is given to the user when the learning part finishes as shown in FIG. 12, interim feedback may be given to the user in the middle of the learning part as in the test part. The same may apply to the drill part. Further, when providing the guidance content in the test part and the drill part, the CPU 21 may cause not only the sound outputter 36 of the wireless earphone 30 to output the voices of the guidance content but also the display 24, which is included in the smartphone 20, to output moving images of the guidance content.

[0094] Further, although in the above embodiment, the exercise guidance system 1 is composed of the motion sensor device 10, the smartphone 20 and the wireless earphone 30, the exercise guidance system 1 may be composed of, for example, the motion sensor device 10 and the wireless earphone 30. In this case, the motion sensor device 10 is configured to be communicably connected with the wireless earphone 30 directly by BLE. In addition, the CPU 11 of the motion sensor device 10 is configured to perform the processes shown by the flowcharts in FIG. 7, FIG. 9, FIG. 10 and FIG. 11.

[0095] It is a matter of course that the detailed configuration and detailed operation of each component of the motion sensor device 10, the smartphone 20 and the wireless earphone 30 of the above embodiment can be changed as appropriate without departing from the scope of the present disclosure.

Examples

Embodiment Construction

[0028]Hereinafter, one or more embodiments of the present disclosure will be described with reference to the drawings. First, the configuration of an exercise guidance system according to an embodiment(s) of the present disclosure will be described with reference to FIG. 1. The exercise guidance system is a system that gives guidance to a user who is running (guidance on user's exercise) to improve his / her running form. As shown in FIG. 1, an exercise guidance system 1 includes a motion sensor device 10, a smartphone 20 and wireless earphone(s) 30.

[0029]The motion sensor device 10 is a wearable terminal that the user of the exercise guidance system 1 uses by wearing it on his / her body (e.g., waist) while running. The smartphone 20 is a portable terminal that the user uses by carrying it while running. The wireless earphone 30 is an ear device that the user uses, like the motion sensor device 10, by wearing it in his / her ear while running. The smartphone 20 is communicably connected ...

Claims

1. An exercise guidance device comprising:a memory that stores a program; andat least one processor that executes the program,wherein the processorobtains a guidance content pertaining to a predetermined form indicator from among guidance contents about a movement of a body of a user in exercise,obtains a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise, andprovides the obtained guidance content to the user who is doing the exercise, by performing, with respect to each guidance timing of guidance timings during the exercise, a series of processes of providing a first guidance content corresponding to the each guidance timing and providing a second guidance content corresponding to a result of the form indicator value that the processor obtains while providing the first guidance content, in order named.

2. The exercise guidance device according to claim 1, wherein the processor provides the first guidance content and the second guidance content, the first guidance content corresponding to the each guidance timing of the guidance timings of a check part in which the processor grasps a current state of the movement of the body of the user, a learning part that comes after the check part and in which the user learns how to move the body based on the current state of the movement of the body of the user, a drill part that comes after the learning part and in which the user actually moves the body and understands how to move the body, and a test part that comes after the drill part and in which the user does the exercise and the processor evaluates the movement of the body of the user in the exercise.

3. The exercise guidance device according to claim 1, wherein the processor obtains the form: indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise and derived based on measured data obtained by a motion sensor worn on the body of the user performing sampling.

4. The exercise guidance device according to claim 2, wherein the test part is provided with at least one interim feedback period in which interim feedback included in the first guidance content is given to the user, before a result feedback period in which result feedback included in the second guidance content is given to the user.

5. The exercise guidance device according to claim 1, wherein the processordetermines a knowledge level of the user about the exercise, andbased on the determined knowledge level, obtains the guidance content for the knowledge level.

6. The exercise guidance device according to claim 1, wherein the processorcauses a display to display the guidance contents, andobtains the guidance content to pertaining the predetermined form indicator, the guidance content being specified by the user from among the guidance contents displayed by the display.

7. The exercise guidance device according to claim 6, wherein the processor obtains, from among guidance contents each being the guidance content pertaining to the predetermined form indicator, a guidance content for the form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise and derived based on measured data obtained by a motion sensor worn on the body of the user performing sampling.

8. The exercise guidance device according to claim 7, wherein the processorobtains a condition level of the user who is doing the exercise based on the derived form indicator value, andobtains, from among the guidance contents each being the guidance content pertaining to the predetermined form indicator, the guidance content for the condition level.

9. An exercise guidance method that is performed by a computer of an exercise guidance device, comprising:obtaining a guidance content pertaining to a predetermined form indicator from among guidance contents about a movement of a body of a user in exercise,obtaining a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise, andproviding the obtained guidance content to the user who is doing the exercise, by performing, with respect to each guidance timing of guidance timings during the exercise, a series of processes of providing a first guidance content corresponding to the each guidance timing and providing a second guidance content corresponding to a result of the form indicator value that the computer obtains while providing the first guidance content, in order named.

10. The exercise guidance method according to claim 9, wherein the providing includes providing the first guidance content and the second guidance content, the first guidance content corresponding to the each guidance timing of the guidance timings of a check part in which the computer grasps a current state of the movement of the body of the user, a learning part that comes after the check part and in which the user learns how to move the body based on the current state of the movement of the body of the user, a drill part that comes after the learning part and in which the user actually moves the body and understands how to move the body, and a test part that comes after the drill part and in which the user does the exercise and the computer evaluates the movement of the body of the user in the exercise.

11. The exercise guidance method according to claim 9, wherein the obtaining of the form indicator value includes obtaining the form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise and derived based on measured data obtained by a motion sensor worn on the body of the user performing sampling.

12. The exercise guidance method according to claim 10, wherein the test part is provided with at least one interim feedback period in which interim feedback included in the first guidance content is given to the user, before a result feedback period in which result feedback included in the second guidance content is given to the user.

13. The exercise guidance method according to claim 9, further comprising determining a knowledge level of the user about the exercise,wherein the obtaining of the guidance content includes, based on the determined knowledge level, obtaining the guidance content for the knowledge level.

14. The exercise guidance method according to claim 9, further comprising causing a display to display the guidance contents,wherein the obtaining of the guidance content includes obtaining the guidance content pertaining to the predetermined form indicator, the guidance content being specified by the user from among the guidance contents displayed by the display.

15. The exercise guidance method according to claim 14, wherein the obtaining of the guidance content includes obtaining, from among guidance contents each being the guidance content pertaining to the predetermined form indicator, a guidance content for the form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise and derived based on measured data obtained by a motion sensor worn on the body of the user performing sampling.

16. The exercise guidance method according to claim 15, further comprising obtaining a condition level of the user who is doing the exercise based on the derived form indicator value,wherein the obtaining of the guidance content includes obtaining, from among the guidance contents each being the guidance content pertaining to the predetermined form indicator, the guidance content for the condition level.

17. A non-transitory computer-readable storage medium storing a program causing a computer of an exercise guidance device to:obtain a guidance content pertaining to a predetermined form indicator from among guidance contents about a movement of a body of a user in exercise,obtain a form indicator value pertaining to the predetermined form indicator, the form indicator value being due to the movement of the body of the user who is doing the exercise, andprovide the obtained guidance content to the user who is doing the exercise, by performing, with respect to each guidance timing of guidance timings during the exercise, a series of processes of providing a first guidance content corresponding to the each guidance timing and providing a second guidance content corresponding to a result of the form indicator value that the computer obtains while providing the first guidance content, in order named.

Images