Information processing device and program recording medium

Abstract

To provide an information processing device capable of giving advice that suits motivation of an object person 41.SOLUTION: An information processing device includes: a goal setting part for setting a first goal to exercise of an object person; an advice generation part for generating first advice to the first object; an output part for outputting the first goal and the first advice; a motivation estimation part for estimating motivation of the object person; and an evaluation part for evaluating the motivation of the object person to the first goal. The advice generation part generates second advice different from the first advice on the basis of an evaluation result of the evaluation part, and the output part outputs the second advice.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing device and a program recording medium. [Background technology]

[0002] 2. Description of the Related Art Devices that provide sports-related advice to users are known. The information processing device described in Patent Document 1 calculates the user's proficiency with an action based on historical information about the action the user performed to achieve a specified goal and attribute information about the user's physical characteristics, and generates advice for achieving the goal based on the proficiency (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2014-228725 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in conventional technologies, advice is generated based on proficiency, so for example, when the proficiency level remains the same, the same advice may continue to be generated, which may result in insufficient advice for the user. [Means for solving the problem]

[0005] In order to solve the above problem, one embodiment is an information processing device comprising a goal setting unit that sets a first goal for a subject's exercise, an advice generation unit that generates first advice for the first goal, an output unit that outputs the first goal and the first advice, a motivation estimation unit that estimates the subject's motivation, and an evaluation unit that evaluates the subject's motivation for the first goal, wherein the advice generation unit generates second advice different from the first advice based on the evaluation result of the evaluation unit, and the output unit outputs the second advice.

[0006] In order to solve the above problem, one embodiment is a program recording medium for recording a program, the program causing a computer to realize a first goal setting function for setting a first goal for a subject's exercise, a first advice generating function for generating first advice for the first goal, a first output function for outputting the first goal and the first advice, a first estimation function for estimating the subject's motivation, a first evaluation function for evaluating the subject's motivation for the first goal, a second advice generating function for generating second advice different from the first advice based on an evaluation result of the first evaluation function, and a second output function for outputting the second advice. [Brief description of the drawings]

[0007] [Figure 1] 1 is a diagram illustrating a schematic configuration example of an information processing system including an information processing device according to an embodiment. [Diagram 2] FIG. 11 is a diagram illustrating an example of a procedure of a process for estimating motivation based on the frequency of checking advice according to the embodiment. [Diagram 3] FIG. 13 is a diagram showing an example of a table used to estimate motivation based on exercise time and exercise intensity according to an embodiment. [Figure 4] FIG. 4 is a diagram showing an example of a procedure of a process performed in the information processing device according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, embodiments will be described with reference to the drawings.

[0009] FIG. 1 is a diagram showing a schematic configuration example of an information processing system 1 including an information processing device 11 according to an embodiment. The information processing system 1 includes an information processing device 11, a sensor unit 21, and a display device 31. 1 also shows a subject 41 who uses the information processing system 1. The subject 41 is a person. The subject 41 may be called, for example, a user.

[0010] Here, in this embodiment, the information processing device 11, the sensor unit 21, and the display device 31 are shown as separate devices, but as another example, one or both of the sensor unit 21 and the display device 31 may be configured to be included in the information processing device 11. In addition, in this embodiment, for convenience of explanation, one subject 41 will be described as a representative, but a plurality of users including the subject 41 may use a common information processing device 11. When there are a plurality of users, for example, each user may be identified by their own arbitrary identification information. The information processing device 11 may be configured as, for example, a cloud server device.

[0011] The sensor unit 21 includes one or more sensors. Each sensor detects information about the subject 41. In this embodiment, the information is information about the movement of the subject 41. Here, the movement of the subject 41 may be, for example, the movement of a body part visible from the outside world, such as the subject's 41 head, torso, arms, hands, legs, feet, etc., or it may be the movement of an internal body part of the subject 41, such as the subject's 41 heart, respiratory system, etc.

[0012] The sensor unit 21 transmits information detected by one or more sensors to the information processing device 11. This information may be, for example, information on the detection results for each sensor, or may be information in which the detection results of two or more different sensors are combined. Note that the communication between the sensor unit 21 and the information processing device 11 may be, for example, wireless communication or wired communication.

[0013] Various sensors may be used for each sensor, such as an Inertial Measurement Unit (IMU), an optical heart rate sensor using Photoplethysmography (PPG), or a Global Positioning System (GPS).

[0014] Here, each sensor is attached to a subject 41 for use. The manner in which it is attached to the subject 41 may be, for example, fixedly attached to the body of the subject 41, or it may be held in the hand of the subject 41, or it may be contained in the clothing or bag of the subject 41. As a specific example, a sensor built into a predetermined device such as a smartphone, a personal computer, a tablet, or a watch may be used, or a dedicated sensor fixedly attached to a predetermined part such as the head, torso, arm, hand, leg, or foot of the subject 41 may be used. The dedicated sensor may be configured to be detachable from the body of the subject 41, for example. In addition, devices such as smartphones may have built-in sensors such as an IMU, a PPG, a GPS, an acceleration sensor, etc. In addition, devices such as smartphones may have built-in pedometers, heart rate monitors, pulse monitors, etc. that use predetermined sensors.

[0015] The display device 31 has a screen for displaying predetermined information. In this embodiment, the information is input to the display device 31 from the information processing device 11. In the present embodiment, the display device 31 may transmit information related to displaying predetermined information or matters received from the subject 41 to the information processing device 11. The display device 31 may include, for example, a touch panel screen having a function of displaying information and a function of receiving operations from the subject 41. Note that the communication between the display device 31 and the information processing device 11 may be, for example, wireless communication or wired communication.

[0016] The display of information by the display device 31 may be controlled by, for example, a predetermined application. As a specific example, the display device 31 may be a device such as a smartphone, a personal computer, a tablet, or a watch.

[0017] Note that the same device may have both the sensor function of the sensor unit 21 and the function of the display device 31. In this case, the sensor unit 21 and the display device 31 may be configured as an integrated device. Furthermore, the same device may have all of the functions of the sensor unit 21, the display device 31, and the information processing device 11. In this case, the sensor unit 21, the display device 31, and the information processing device 11 may be configured as an integrated device.

[0018] The information processing device 11 includes an exercise information acquisition unit 111 , a determination unit 112 , a motivation estimation unit 113 , an evaluation unit 114 , a goal setting unit 115 , an advice generation unit 116 , an output unit 117 , and a memory unit 118 . In this embodiment, the information processing device 11 is configured using a computer. In the information processing device 11, a processor such as a CPU (Central Processing Unit) executes a predetermined program to perform various processes and controls.

[0019] In addition, in FIG. 1, arrows are used to show an example of the flow of information exchange between the sensor unit 21, the display device 31, and each component of the information processing device 11. However, this is not necessarily limited to this example, and information may be exchanged between any components according to the needs of the information processing.

[0020] The exercise information acquisition unit 111 acquires information transmitted from the sensor unit 21 and received by the information processing device 11, and based on the information, outputs information regarding the exercise performed by the subject 41 to one or both of the motivation estimation unit 113 and the goal setting unit 115. Here, the exercise information acquisition unit 111 may, for example, output the information acquired from the sensor unit 21 directly to the motivation estimation unit 113 or the goal setting unit 115, or may output information resulting from processing the information to the motivation estimation unit 113 or the goal setting unit 115. In this embodiment, the information acquired by the exercise information acquisition unit 111 is information related to the movement of the subject 41, and is used as information related to the exercise of the subject 41 in this embodiment.

[0021] Here, as one example, the exercise information acquisition unit 111 may acquire information about a general exercise performed by the subject 41, or as another example, may acquire information about a specific exercise performed by the subject 41. That is, the exercise referred to in this embodiment may be a general exercise or a specific exercise. The particular exercise may be, for example, the exercise of a particular sport.

[0022] The exercise performed by the subject 41 is not particularly limited, and may be, for example, a sport such as a marathon, golf, tennis, or soccer. The exercise may also include, for example, muscle training for personal health. Note that personal muscle training may also be considered as a type of sport. Furthermore, the exercise may or may not include walking or running in daily life.

[0023] Note that the information processing device 11 may determine and distinguish between a state in which the subject 41 is performing a specific exercise and a state in which the subject 41 is not performing a specific exercise, or may not need to distinguish between the two. When the information processing device 11 determines whether the subject 41 is performing a specific exercise or not, the function for making such a determination may be provided in any component, and may be provided, for example, in the exercise information acquisition unit 111, the judgment unit 112, or the motivation designation unit 113.

[0024] As an example, when the sensor of the sensor unit 21 attached to the subject 41 is on, the subject 41 may be considered to be in a state of performing a specific exercise. In other words, when information from the sensor is input to the information processing device 11, the subject 41 may be considered to be in a state of performing a specific exercise. In this embodiment, when the sensor of the sensor unit 21 is not attached to the subject person 41, the sensor is turned off and information from the sensor is not input to the information processing device 11. As a specific example, if the specific exercise is a marathon race, for example, when subject 41 starts running the marathon, he or she attaches a sensor to subject 41's body and turns on the sensor, and when subject 41 finishes running the marathon, he or she turns off the sensor.

[0025] As another example, when a specific movement of the subject 41 is detected by a sensor of the sensor unit 21, the subject 41 may be considered to be in a state of performing a specific exercise. The specific movement of the subject 41 may be detected by, for example, a specific sensor. As a specific example, if the specific exercise is a marathon race, for example, when the information processing device 11 determines that the subject 41 is running based on sensor detection information, the subject 41 may be deemed to be in a state of running a marathon. In addition, the information processing device 11 may determine whether or not the subject 41 is making a specific movement. For example, the information processing device 11 may constantly monitor the specific movement of the subject 41, and when the detection value of a sensor corresponding to the movement exceeds a predetermined threshold, it may determine that the subject 41 is performing a specific movement, and in other cases, it may determine that the subject 41 is not performing a specific movement.

[0026] As another example, a configuration may be used in which the subject 41 directly or indirectly inputs information indicating the time to start a specific exercise and the time to end the exercise to the information processing device 11. This input may be performed, for example, by the subject 41 directly operating the information processing device 11, or by the subject 41 operating a device such as a smartphone and transmitting information from the device to the information processing device 11. It should be noted that the time to start a particular exercise and the time to end the exercise do not necessarily need to be input to the information processing device 11 at the same time, and each time may be input to the information processing device 11 at different times. As a specific example, when the specific exercise is a marathon race, information on the timing at which the marathon begins and information on the timing at which the marathon ends may each be input to the information processing device 11.

[0027] The determination unit 112 acquires information transmitted from the sensor unit 21 and received by the information processing device 11, and makes a determination regarding the condition of the subject 41 based on the information. The determination unit 112 outputs information on the determination result to the motivation estimation unit 113. The determination unit 112 may also output information on the determination result to the evaluation unit 114. Here, the determination may be a determination regarding various conditions. The determination unit 112 may be called, for example, a state determination unit or a state measurement unit.

[0028] In this embodiment, an ideal goal is set as an ideal target for the exercise of the subject 41. The ideal goal may be set by inputting it by the subject 41 or another person using a predetermined application, for example. As the application, for example, an application of the information processing device 11 may be used, or an application of another device may be used. The other device may be, for example, the sensor unit 21 or the display device 31. As another example, the ideal goal may be automatically set by the information processing device 11 or another device. The other device may be, for example, the sensor unit 21 or the display device 31. Various methods may be used to automatically set the ideal goal, and for example, a method may be used in which the ideal goal is obtained and set by calculation based on information about the subject 41's body, such as the age of the subject 41, or a change in the information.

[0029] Here, the ideal goal may be set arbitrarily for each type of exercise, for example, and goals such as time, score, or load to be cleared may be set, and further, a goal for the period until such goal is achieved may be set. As a specific example, when the exercise of the subject 41 is a marathon race, an ideal target value for the marathon time may be set as the ideal goal, and further, an ideal period to achieve the time may be included in the ideal goal. As an example, the information processing device 11 may set, based on physical information such as the age of the subject 41, a general fastest record time or average record time in a marathon that corresponds to the physical information, as the ideal goal.

[0030] In the present embodiment, the function of setting an ideal goal in the information processing device 11 is provided in the goal setting unit 115. For example, when automatically setting an ideal goal, the goal setting unit 115 may refer to one or both of the information from the exercise information acquisition unit 111 and the information of the determination result by the determination unit 112. As another example, the functionality for setting an ideal target may be provided in the judgment unit 112, or in any other component shown in the example of FIG. 1, or may be provided as an independent component not shown in the example of FIG. 1.

[0031] In this embodiment, an intermediate goal, which is an intermediate target, is set for the exercise of the subject person 41. In this embodiment, the intermediate goal is set by the goal setting unit 115 of the information processing device 11. Here, the intermediate goal is an intermediate goal before achieving the ideal goal, and corresponds to a state between the current state of the subject 41 and the ideal goal state.

[0032] As a first example, the determination unit 112 may determine the current state of the subject 41 with respect to an ideal target state regarding the exercise of the subject 41. As a second example, the determination unit 112 may determine an item required for achieving an ideal target state regarding the exercise of the subject 41. The item may be an item regarding the way the subject 41 moves. As a third example, the determination unit 112 may determine whether or not an intermediate goal state has been achieved in relation to the exercise of the subject 41, and if the state has been achieved, determine the period until the state is achieved. In each of these determinations, for example, the deviation between a target state, such as an ideal target or an intermediate target, and the current state of the subject 41 may be determined.

[0033] As a specific example, a case where the exercise of the subject 41 is a marathon race will be described. Assume that the ideal goal is for subject 41 to run 42.195 km in 4 hours. In the first example of the judgment, the judgment unit 112 may judge the time measured using the detection result of the sensor while the subject 41 is running a marathon as the current state. The current time does not necessarily have to be the exact current time, and for example, a slightly past time such as the time from the previous marathon may be regarded as the current time. The sensor may include a GPS sensor that detects position information. The determination unit 112 does not necessarily need to determine the current state strictly, and may, for example, regard the current state estimated by a predetermined estimation method as the determination result. As a specific example, an estimation method may be used that estimates a time based on the amount of exercise of a marathon run by the subject 41.

[0034] In the second example, the item required to achieve the ideal target state may be a form that improves the time in a marathon and approaches the ideal state. Details of the form may include, for example, ground contact time, which is generally considered to be shorter, or vertical movement, which is generally considered to be smaller. Note that other items may be used as such items. Such items may be predefined, for example, for each sport.

[0035] In the determination of the third example, the period required for the subject 41 to achieve the previous intermediate goal state is used as the period until the previous intermediate goal state is achieved. In this embodiment, the period until the achievement of the previous intermediate goal state may be determined, for example, as the period from the presentation of the latest advice presented before the achievement of the previous intermediate goal state to the time when the previous intermediate goal state is achieved. As another example, when the subject 41 starts exercising at an early stage and there is no intermediate goal closer to the start time than the previous intermediate goal, that is, when the previous intermediate goal is the first intermediate goal since the start time, the period from the start time to the achievement time of the state of the previous intermediate goal may be determined. Also, when there is an intermediate goal before the previous intermediate goal, which is the intermediate goal before the previous intermediate goal, the period from the achievement time of the state of the intermediate goal before the previous to the achievement time of the state of the previous intermediate goal may be determined.

[0036] The motivation estimation unit 113 estimates the motivation of the subject 41. In this embodiment, the motivation estimation unit 113 estimates the motivation of the subject 41 based on one or more of the information from the exercise information acquisition unit 111, the information from the determination unit 112, and the information from the display device 31. The motivation estimation unit 113 outputs information on the motivation estimation result to the evaluation unit 114.

[0037] In this embodiment, the motivation estimation unit 113 estimates the motivation of the subject 41 based on one or more of a plurality of parameters regarding the exercise of the subject 41. These parameters may include, for example, one or more of exercise time, number of exercises, exercise frequency, exercise intensity, the period required to achieve the previous intermediate goal, and frequency of checking advice. As an example, the parameters may be, but are not limited to, four parameters, namely, exercise time, either number of exercises or exercise frequency, exercise intensity, and frequency of checking advice. It is to be noted that both the number of times of exercise and the frequency of exercise may be used, or either one of the number of times of exercise and the frequency of exercise may be used.

[0038] The motivation estimation unit 113 has a function of generating predetermined exercise-related information. In this embodiment, the exercise-related information is exercise time, either the number of times of exercise or the frequency of exercise, exercise intensity, and the period required to achieve the previous intermediate goal state.

[0039] As the exercise time, for example, the exercise time for one day may be used, or the exercise time for another period may be used. The motivation estimation unit 113 calculates, for example, a time during which there is movement of a certain strength or more from the measurement time of the sensor of the sensor unit 21, and regards this as the exercise time. As the time during which there is movement of a certain strength or more, for example, a time during which the acceleration or angular velocity detected by a sensor such as an IMU is equal to or greater than a certain value may be used.

[0040] The number of times of exercise may be, for example, the number of times of exercise in a certain period of time. The certain period of time may be any period of time. The motivation estimation unit 113 calculates the number of times of exercise based on, for example, information on the measurement date of the sensor of the sensor unit 21. As a specific example, the motivation estimation unit 113 may estimate that the number of times of exercise is large when the number of times of exercise in a week is seven or more.

[0041] The frequency of exercise may be, for example, the number of times the exercise is performed in a certain period of time. The certain period of time may be any period of time. The motivation estimation unit 113 calculates the frequency of exercise based on, for example, information on the measurement date of the sensor of the sensor unit 21. As a specific example, the motivation estimation unit 113 may estimate that the exercise frequency is high when there are seven measurement days in a week on which the subject 41 exercised.

[0042] As the exercise intensity, for example, the exercise load for one day may be used, or the exercise load for another period of time may be used. The motivation estimation unit 113 may calculate the exercise load based on, for example, one or more of the acceleration or angular velocity detected by an IMU sensor, the heart rate detected by a heart rate meter, or the pulse detected by a pulse meter. As a specific example, the motivation estimation unit 113 may calculate the average pulse rate of the subject 41 during exercise, and if the average pulse rate is higher than a predetermined threshold, estimate that the exercise load is high, i.e., the exercise intensity is high.

[0043] The period required to achieve the previous intermediate goal state may be, for example, calculated as the number of days from the date of providing advice to the subject 41 to the date of achieving the previous intermediate goal state. This calculation may be performed, for example, based on the advice history of the application that provides the advice. The motivation estimation unit 113 calculates the number of days required to achieve the previous intermediate goal state based on the judgment result of whether or not the previous intermediate goal state is satisfied from the measurement data of a predetermined sensor. The judgment result by the judgment unit 112 may be used as the judgment result. As a specific example, the motivation estimation unit 113 may estimate that the period is short if it took three days to achieve the previous intermediate goal state, and may estimate that the period is long if it took one month.

[0044] The motivation estimation unit 113 has a function of generating predetermined behavioral information regarding the subject 41. In this embodiment, the behavioral information is the frequency of advice confirmation. The frequency of checking the advice may be based on the number of times the screen displaying the advice is opened. The number of times may be calculated based on the operation history of the application displaying the advice. The advice may be displayed together with the display of the goal, for example. As a specific example, the motivation estimation unit 113 may calculate the number of times a corresponding screen is confirmed in a day as the advice confirmation frequency. Here, when generating the advice confirmation frequency, the motivation estimation unit 113 may refer to information such as the timing, number of times, and frequency at which advice was generated by the advice generation unit 116, for example. For example, the number of times the advice has been confirmed may be used in addition to or instead of the advice confirmation frequency.

[0045] In this embodiment, information regarding the movement of the subject 41 is detected as movement information by the sensor of the sensor unit 21, and information other than the movement of the subject 41 is detected as behavior information by another application. The behavior information may be generated in response to, for example, a predetermined operation being performed in a predetermined application by the subject 41. The predetermined operation may be an operation for viewing advice, or the like. In this embodiment, the function of the sensor used to detect exercise information and the function of the application used to detect behavioral information are separate functions, but both of these functions may be provided in the same device, such as a smartphone.

[0046] Here, in this embodiment, for ease of explanation, a case is shown in which the motivation estimation unit 113 generates predetermined exercise-related information based on the exercise information acquired by the exercise information acquisition unit 111 and, if necessary, information from the judgment unit 112, and generates behavioral information based on information such as the operation history from the display device 31. In this manner, in this embodiment, for ease of explanation, a distinction is made between exercise information and exercise-related information, and exercise-related information is generated from exercise information; however, since exercise-related information is also information regarding the exercise of subject 41, it may also be considered to be included in exercise information. In addition, the exercise information and the exercise-related information may be called by other names, for example.

[0047] In this embodiment, the motivation estimation unit 113 estimates motivation by dividing it into a plurality of stages. Here, the number of motivation levels may be arbitrary, for example, three levels such as high, medium, and low may be used, or a larger number of levels such as 10 may be used. Also, two motivation levels may be used.

[0048] As a general trend, it can be estimated that those who exercise for a longer period of time are more motivated, and those who exercise for a shorter period of time are less motivated. As a general tendency, it can be estimated that those who exercise more frequently or more often are more motivated, and those who exercise less frequently or less often are less motivated. As a general trend, it can be estimated that with regard to exercise intensity, a higher load means more motivation, and a lower load means less motivation.

[0049] As a general trend, it can be estimated that those who check advice more frequently are more motivated, and those who check advice less frequently are less motivated. As a general trend, it can be assumed that those who took a shorter time to achieve their previous intermediate goal are more motivated, and those who took a longer time to achieve their previous intermediate goal are less motivated. However, depending on the level of the intermediate goal, it may be difficult for the subject 41 to achieve it, and it may be better to make a different estimation result.

[0050] In one embodiment, the motivation estimation unit 113 may determine the motivation estimation result based on the value of one of the multiple parameters. In this case, for example, the motivation estimation result may be determined according to the magnitude relationship between the parameter value and one or more predetermined threshold values.

[0051] FIG. 2 is a diagram illustrating an example of a procedure of a process for estimating motivation based on the frequency of checking advice according to the embodiment. In the example of FIG. 2, the motivation estimation unit 113 performs the processes of steps S1 to S6.

[0052] In step S1, the motivation estimation unit 113 reads out an operation history of an application for a certain period of time that is operated by the subject person 41 to confirm advice, and then proceeds to the process of step S2.

[0053] In step S2, the motivation estimation unit 113 judges whether the subject 41 checks the advice at least once a day based on the read operation history. If the motivation estimation unit 113 judges that the subject 41 checks the advice at least once a day, the result is YES as shown in Fig. 2, and the process proceeds to step S3, otherwise the result is NO as shown in Fig. 2, and the process proceeds to step S4. Here, the threshold used is checking advice at least once a day. In this embodiment, when the advice is viewed by the subject person 41, it is considered that the subject person 41 has confirmed the advice. In step S3, the motivation estimation unit 113 estimates that the motivation is high, and ends the process of this flow.

[0054] In step S4, the motivation estimation unit 113 judges whether the subject 41 checks the advice at least once a week based on the read operation history. If the motivation estimation unit 113 judges that the subject 41 checks the advice at least once a week, the result is YES as shown in Fig. 2, and the process proceeds to step S5, otherwise the result is NO as shown in Fig. 2, and the process proceeds to step S6. Here, checking advice at least once a week is used as the threshold.

[0055] In step S5, the motivation estimation unit 113 estimates that the motivation is medium, and ends the process of this flow. Note that medium may also be called normal, for example. In step S6, the motivation estimation unit 113 estimates that motivation is low, and ends the process of this flow.

[0056] Here, the process flow shown in FIG. 2 is an example, and other process flows may be used as the process flow for estimating motivation. For example, the motivation estimation unit 113 may determine whether the subject 41 checks advice at least once a month, and if it determines that the subject 41 does not check advice at least once a month, may estimate that the subject 41 has low motivation.

[0057] In another embodiment, the motivation estimation unit 113 may determine the motivation estimation result based on the values ​​of two or more parameters among the multiple parameters. In this case, for example, the motivation estimation result may be determined according to the magnitude relationship between a combination of two or more parameters and a predetermined threshold value.

[0058] FIG. 3 is a diagram showing an example of a table T1 used to estimate motivation based on exercise time and exercise intensity according to the embodiment. The information in table T1 may be stored in storage unit 118, for example. In the example of table T1, there are three columns for exercise time: 21 hours or more per week, 10 to 21 hours per week, and 10 hours or less per week. Here, 10 to 21 hours represents a time period longer than 10 hours and shorter than 21 hours. Moreover, in the example of table T1, there are three columns for exercise intensity: high, medium, and low.

[0059] In this example, once both the exercise time and the exercise intensity are determined, one field is determined and an estimated result of motivation is determined. In the example of table T1, either "high motivation" indicating high motivation, "medium motivation" indicating medium motivation, or "low motivation" indicating low motivation is entered in each column.

[0060] In this manner, the motivation estimation unit 113 may estimate motivation corresponding to a combination of exercise time and exercise intensity based on table T1. In the example of FIG. 3, the case where motivation is estimated based on two parameters is shown, but as another example, motivation may be estimated based on three or more parameters.

[0061] For example, when estimating motivation using one parameter such as exercise time, even if the subject 41 only does easy exercise with low intensity for a long time, the subject will be estimated to be highly motivated because of the long exercise time. Therefore, by estimating motivation using two parameters, exercise time and exercise intensity, as in this example, it is possible to improve the accuracy of the estimation. In the example of Figure 3, for example, if high-intensity exercise is performed for 21 hours or more per week, motivation is estimated to be high, and if medium-intensity exercise is performed for 10 to 21 hours per week, motivation is estimated to be medium.

[0062] As another aspect, the motivation estimation unit 113 may determine the estimation result of motivation by weighting the values ​​of two or more parameters among the multiple parameters and calculating an overall score. Here, the weighting may include equal weighting. Furthermore, the range of the score is not particularly limited, and for example, a linear range of 0 to 100 points may be used, or another range of scores may be used.

[0063] As an example, the motivation estimation unit 113 may assign equal scores to all of the parameters. As a specific example, the motivation estimation unit 113 may score each of the four parameters out of a maximum of 25 points, and add these up to calculate a maximum score of 100 points. These four parameters may be, for example, the duration of exercise, the number of times exercised or the frequency of exercise, the intensity of exercise, and the frequency of checking advice.

[0064] As another example, the motivation estimation unit 113 may increase the weight of a parameter that is considered to be particularly directly related to motivation among the multiple parameters and perform scoring. Note that the weight of each parameter may be set in advance, for example. As a specific example, when four parameters are used, namely, exercise time, either the number of times of exercise or the frequency of exercise, exercise intensity, and frequency of checking advice, the motivation estimation unit 113 may increase the score weighting of the exercise time involving actual exercise, the number of times of exercise or the frequency of exercise, and exercise intensity, each of which is weighted to a maximum of 30 points, and the frequency of checking advice may be weighted to a maximum of 10 points, to calculate a total score of 100 points.

[0065] In addition, this method of calculating a motivation score for each parameter is thought to make it easier to calculate an overall motivation score compared to a method that determines motivation on a scale such as high, medium, or low for each parameter.

[0066] Here, in this embodiment, the motivation estimation unit 113 estimates the motivation of the subject 41. However, for example, the motivation estimation unit 113 may further estimate the proficiency of the subject 41 with respect to the goal. The proficiency may be estimated based on the exercise history of the subject 41 with respect to the goal. The goal is an ideal goal the first time, and is an intermediate goal set previously other than the first time. For example, proficiency may be used to adjust motivation. It should be noted that proficiency does not necessarily have to be used.

[0067] The evaluation unit 114 performs a predetermined evaluation based on the information from the motivation estimation unit 113, thereby generating an evaluation result based on the motivation estimation result. Here, when performing the evaluation, the evaluation unit 114 may refer to the information from the determination unit 112 as well as the information from the motivation estimation unit 113. The evaluation unit 114 outputs information on the evaluation result to the goal setting unit 115 .

[0068] Here, the evaluation unit 114 may use various methods for the evaluation. For example, the evaluation unit 114 may evaluate whether the motivation of the subject 41 is appropriate for the level of the goal, or the degree of appropriateness, based on the estimated result of the motivation of the subject 41 for a predetermined goal. As the goal, for example, an ideal goal or an intermediate goal may be used.

[0069] As a specific example, consider a case where a goal is set to run a full marathon in four hours, and the estimated motivation for the goal level is one of high, medium, and low. The goal is, for example, an ideal goal. In this case, when the estimated result of motivation is high, the evaluation unit 114 may evaluate that motivation is sufficient for the level of the goal. Also, for example, when the estimated result of motivation is medium, the evaluation unit 114 may evaluate that motivation is slightly insufficient for the level of the goal. Also, for example, when the estimated result of motivation is low, the evaluation unit 114 may evaluate that motivation is insufficient for the level of the goal.

[0070] As another specific example, consider a case where a goal is set to run a full marathon in five hours, and the estimated motivation for the goal level is one of high, medium, and low. The goal is, for example, an intermediate goal, which is a goal of a lower level than the ideal goal. In this case, when the estimated result of motivation is high, the evaluation unit 114 may evaluate that the motivation is sufficient for the level of the goal. Also, when the estimated result of motivation is medium, the evaluation unit 114 may evaluate that the motivation is sufficient for the level of the goal. Also, when the estimated result of motivation is low, the evaluation unit 114 may evaluate that the motivation is slightly insufficient for the level of the goal.

[0071] The goal setting unit 115 sets a predetermined goal based on one or both of the information from the exercise information acquisition unit 111 and the information from the evaluation unit 114 . The goal setting unit 115 outputs information about the set goal to the advice generating unit 116 .

[0072] Here, the set target may be, for example, an ideal target or an intermediate target. There may also be cases where two or more intermediate goals are set. As an example, the goal setting unit 115 may first set an ideal goal, and then set intermediate goals with respect to the ideal goal.

[0073] As another example, the goal setting unit 115 may first set an ideal goal, then set a first intermediate goal for the ideal goal, and then set a second intermediate goal for the first intermediate goal. Similarly, the goal setting unit 115 may set three or more intermediate goals. In this embodiment, for the second intermediate target, which is the second intermediate target, the previous target is the first intermediate target, which is the first intermediate target. Similarly, for the third intermediate target, which is the third intermediate target, the previous target is the second intermediate target, which is the second intermediate target. The same applies to the subsequent intermediate targets.

[0074] The intermediate goal is a goal that corresponds to a state between the current state of the subject 41 and the ideal goal state, and is a goal on the way to achieving the ideal goal. The goal setting section 115 may determine the current state of the subject 41 based on information from the exercise information acquisition section 111, for example. As another example, information on the result of the judgment of the current state of the subject 41 by the judgment section 112 may be output from the judgment section 112 to the goal setting section 115 and referred to by the goal setting section 115.

[0075] The goal setting unit 115 sets an ideal goal based on, for example, information from the exercise information acquisition unit 111. That is, the goal setting unit 115 sets an ideal goal based on information on the exercise of the subject 41. As another example, the goal setting unit 115 may set an ideal goal based on other information, or may set a predetermined ideal goal.

[0076] The goal setting unit 115 sets an intermediate goal based on, for example, information from the evaluation unit 114. That is, the goal setting unit 115 sets an intermediate goal based on an evaluation result based on an estimation result of the motivation of the subject 41. Generally, the intermediate goal is set based on the motivation for the previous goal. As an example, a more difficult intermediate goal may be set for a subject 41 who exercises more, since the subject 41 is considered to be more motivated.

[0077] Furthermore, an intermediate goal may be set taking into consideration the time it took to achieve the previous goal. In this embodiment, the period required to achieve the previous goal may be determined by the determination unit 112, referred to in the estimation by the motivation estimation unit 113, and reflected in the evaluation result by the evaluation unit 114. As another example, a configuration may be used in which information on the result of the determination by the determination unit 112 is output from the determination unit 112 to the goal setting unit 115. In this case, the goal setting unit 115 may refer to the information from the determination unit 112 when setting a goal.

[0078] In this way, how close the intermediate goal level should be set to the ideal goal level may be determined by taking into consideration two parameters, for example, the motivation of the subject 41 and the time it took to achieve the previous intermediate goal. In this case, when the subject 41 achieves the intermediate goal, the next intermediate goal is determined according to the motivation of the subject 41 and the period until the achievement of the previous intermediate goal.

[0079] For example, if the subject 41 was highly motivated toward the previous intermediate goal, the next intermediate goal may be set to be closer to the ideal goal than if the subject's motivation was not high. However, if the subject 41 has been exercising continuously but it took a long time to achieve the intermediate goal, or if the intermediate goal is not achieved, the goal setting unit 115 may determine that the subject 41 is motivated but at a level where it is difficult to achieve the goal, and may adjust the next intermediate goal to be closer to the current state of the subject 41.

[0080] On the other hand, for example, if the subject 41 was less motivated toward the previous intermediate goal, the next intermediate goal may be set to be closer to the current state of the subject 41 than if the motivation was not low. However, if the time period until the intermediate goal is achieved is short, the goal setting unit 115 may determine that the subject 41 is not motivated but is at a level where the goal can be easily achieved, and adjust the next intermediate goal to be closer to the ideal goal.

[0081] In this way, the goal setting unit 115 judges the ease of goal achievement based on, for example, the motivation of the subject 41 and the time it took to achieve the previous intermediate goal, and sets the next goal based on the judgment result so that the subject 41 can achieve the goal while maintaining the subject 41's motivation.

[0082] As a concrete example, consider the case where your goal is to improve your marathon time. In this case, for example, the next intermediate goal may be set using the rate [%] of approach to the ideal goal with respect to the current state of the subject 41. As an example, the current state of the subject 41 is a time of 6 hours, which is regarded as 0[%]. Also, the ideal target state is a time of 4 hours, which is regarded as 100[%]. In this case, if the next intermediate goal is a time of 5 hours and 55 minutes, the percentage [%] approaching the ideal target is approximately 4.2[%].

[0083] Here, in this embodiment, when an ideal goal is set initially, a next intermediate goal is not set. However, as another example, when setting an initial ideal goal, the goal setting unit 115 may set a next intermediate goal based on the ideal goal at the same time or immediately after the initial ideal goal is set. In this case, the next intermediate goal may be a goal that corresponds to the result of equally dividing the change in state until the ideal goal is achieved over a predetermined period of time. For example, only in the case of first-time use, the goal setting unit 115 may set an intermediate goal that is equally divided according to the result of dividing the state change until the ideal goal is achieved by the period based on the ideal goal and its period.

[0084] As a specific example, the current state of the subject 41 is a time of 6 hours, which is regarded as 0[%]. The ideal target state is a time of 4 hours, which is regarded as 100[%]. Also, the period from the present to the achievement of the ideal target is set to 2 years. In this case, the intermediate goal is set so that the ideal goal will be achieved in two years. That is, in the even division, by calculating {120 minutes / 24 months}, if the time is reduced by 5 minutes per month, the ideal goal will be achieved in two years. Therefore, the goal setting unit 115 sets the intermediate goal of a time of 5 hours and 55 minutes in one month as the next goal.

[0085] In reality, there may be cases where the subject 41 is unable to achieve the next intermediate goal. In this case, the goal setting unit 115 may perform one or both of a process of changing the next intermediate goal and a process of changing the deadline by which the next intermediate goal should be achieved. For example, if the deadline for the next intermediate goal has passed without the subject 41 being able to achieve the next intermediate goal, the goal setting unit 115 may change the next intermediate goal and postpone the deadline, etc., based on the motivation of the subject 41 and the period of time it took to achieve the previous intermediate goal. In this case, the level of the changed next intermediate goal may be, for example, lower than the level of the next intermediate goal before the change, that is, it may be a level that is easier to achieve.

[0086] In this embodiment, the motivation of the subject 41 is reflected in the evaluation result by the evaluation unit 114, and the goal setting unit 115 sets an intermediate goal based on the information of the evaluation result. As another example, the goal setting unit 115 may set an intermediate goal based on information on the estimation result by the motivation estimation unit 113, together with information on the evaluation result by the evaluation unit 114, or instead of information on the evaluation result by the evaluation unit 114. In this case, the information on the estimation result by the motivation estimation unit 113 may be configured to be output from the motivation estimation unit 113 to the goal setting unit 115. As another example, when proficiency information is required separately from motivation information, the goal setting section 115 may set an intermediate goal using the proficiency information together with the motivation information.

[0087] The advice generating unit 116 generates a predetermined advice, and outputs information on the generated advice to the output unit 117. Here, as the advice, various advice contents may be used, for example, advice including advice contents for achieving the ideal goal or the next goal which is an intermediate goal may be used.

[0088] In this embodiment, the advice generating unit 116 generates advice based on information from the goal setting unit 115 . Here, the advice generating unit 116 may generate advice by, for example, referring to one or more of the output information from the exercise information acquiring unit 111, the output information from the judgment unit 112, the output information from the motivation estimating unit 113, and the output information from the evaluation unit 114 together with the information from the goal setting unit 115 or instead of the information from the goal setting unit 115. In this case, the information referred to by the advice generating unit 116 may be configured to be output to the advice generating unit 116 from a configuration unit that outputs the information. The configuration unit is one or more of the exercise information acquiring unit 111, the judgment unit 112, the motivation estimating unit 113, and the evaluation unit 114. Furthermore, the advice generator 116 may generate the next advice based on, for example, past advice, which may be, for example, the previous advice.

[0089] In general, the advice generating unit 116 may perform one or more of the following processes on the advice to be output: changing the difficulty level of the advice, changing the number of key points of the advice, changing the expression of the advice, or presenting success stories of other users. Here, the other users may be, for example, people who have previously tried and succeeded in an exercise similar to the exercise being performed by the subject 41.

[0090] For example, consider a case where the advice generating unit 116 generates advice for the next intermediate goal by directly or indirectly taking into account at least the motivation of the subject person 41. As an example, the advice generator 116 may generate advice based only on motivation. As a specific example, the advice generating unit 116 may present advice with varying difficulty and number of key points according to motivation. The difficulty of the advice may be made more difficult for those with high motivation, and easier for those with low motivation. The number of key points may be made more for those with high motivation, and fewer for those with low motivation. Generally, the lower the level of difficulty of the advice, the easier it is to understand. Also, fewer points are usually easier to implement.

[0091] As another example, the advice generator 116 may generate advice based on motivation and other information. As the other information, various information may be used, for example, one or more of information among an intermediate goal, a current state of the subject 41, items for achieving an ideal goal, etc. Depending on these pieces of information, the expression of the advice may be embodied.

[0092] As a concrete example, let us consider the case of a marathon. When the advice generating unit 116 generates advice based only on motivation, as an example, the advice may be expressed as "run 3 km twice in 30 minutes," which allows the user to understand what goal to aim for when exercising. On the other hand, when the advice generating unit 116 generates advice according to motivation and other information, for example, the advice may be expressed as "Because the vertical movement is large at 30 cm, try to keep it at 20 cm, and run 3 km twice in 30 minutes," thereby expressing more specific items for achieving the goal. Note that the advice in this example takes into account the current state of the subject 41 and is advice that expresses in detail what further needs to be done in consideration of the items for realizing the achievement of the ideal goal.

[0093] Furthermore, for example, when the subject 41 is not motivated, the advice generating unit 116 may find a case where the subject 41 succeeded in a state similar to that of the subject 41 based on the current state of the subject 41 and the goal achievement history of other users, and present the found case as a success case, thereby motivating the subject 41. In this presentation, for example, with respect to the success cases of other users, information such as a goal representing an ideal goal or intermediate goal, the state of the other user before receiving advice, and the period for which the other user achieved the goal may be presented. Here, the other user may represent a subject other than the subject 41, for example, a person other than the subject 41 who is exercising the same sport as the subject 41. Note that such presentation may be made, for example, when the advice generating unit 116 generates advice based only on motivation, or when the advice generating unit 116 generates advice based on motivation and other information, or in both of these cases. By presenting in this manner, the advice generating unit 116 can, for example, introduce to a less motivated subject 41 a situation in which another user with an ability value close to that of the subject 41 achieved a goal through advice, and can inform the subject 41 of how that other user has grown, etc.

[0094] The output unit 117 outputs the information from the advice generating unit 116 to the display device 31. As a result, the information is displayed on the screen of the display device 31 and is notified to the target person 41 or the like. In this embodiment, the output unit 117 outputs information from the advice generation unit 116 to the display device 31, but the output unit 117 may output other information to the display device 31, thereby displaying the information on the display device 31.

[0095] In addition, in this embodiment, for convenience of explanation, one display device 31 is shown, but, for example, multiple display devices including display device 31 may be provided in the information processing system 1, and in this case, the output unit 117 may output the same information or different information to each of the two or more display devices.

[0096] The storage unit 118 has a function of storing various types of information. In this embodiment, the storage unit 118 starts storing information about the subject 41 from the initial state of the subject 41, and stores and holds information about the subject 41 until the subject 41 achieves the ideal goal. Such information may be, for example, information that represents the situation from the initial state of the subject 41 to the time when the subject 41 continues to exercise, such as a predetermined sport, thereby achieving an intermediate goal and finally achieving the ideal goal. Such information may be called history information. The history information is not limited to the information shown in this example, and may be composed of any information. Note that there may be cases where the subject 41 is ultimately unable to achieve the ideal goal.

[0097] The historical information may include, for example, one or more of the history of operations input from a specified application, ideal goals, intermediate goals, exercise information, behavioral information, exercise-related information, the condition of the subject 41, the motivation of the subject 41, the status of goal achievement, advice presented to the subject 41, and the like. Here, the status of goal achievement may be, for example, information such as the number of days divided into intermediate goals or the number of days remaining until the achievement of past goals. In this embodiment, such history information is stored and saved in the storage unit 118.

[0098] FIG. 4 is a diagram showing an example of a procedure of processing performed in the information processing device 11 according to the embodiment. In the example of FIG. 4, the information processing device 11 performs the processes of steps S21 to S32. In the processing flow of this example, the processing of steps S21 to S32 is carried out in order.

[0099] In step S21, the exercise information acquisition section 111 acquires information regarding the exercise of the subject 41. In step S22, the goal setting unit 115 sets a first goal based on the information about the exercise acquired by the exercise information acquisition unit 111. In this example, the first goal is an ideal goal. In step S23, the advice generator 116 generates advice for the first goal. Note that this advice may be called, for example, first advice. In step S24, the output unit 117 outputs information representing the set first goal and the generated advice via the display device 31. The subject 41 can confirm the information.

[0100] In step S25, the motivation estimation unit 113 estimates the motivation of the subject 41. In step S26, the evaluation unit 114 evaluates the motivation for the first goal. In step S27, the goal setting unit 115 sets a second goal according to the result of the evaluation. In this example, the second goal is the first intermediate goal. In step S28, the advice generator 116 generates advice for the second goal. Note that this advice may be called, for example, second advice. In step S29, the output unit 117 outputs information representing the set second goal and the generated advice via the display device 31. The subject 41 can confirm the information.

[0101] In step S30, the determination unit 112 determines whether the second goal has been achieved based on the information on the exercise. Here, it is assumed that the subject 41 has achieved the second goal. In step S31, the motivation estimation unit 113 estimates motivation based on the period of time taken to achieve the second goal. Here, the evaluation unit 114 evaluates the motivation for the second goal. In step S32, the goal setting unit 115 sets a third goal according to the result of the evaluation. In this example, the third goal is a second intermediate goal.

[0102] Although not shown in FIG. 4, after step S32, the information processing device 11 generates and outputs advice for each goal from the third goal onwards, and sets the next goal as necessary, and finally sets the first goal, which is an ideal goal, and the ideal goal is achieved. For example, the first goal, which is an ideal goal, may be set as a fourth goal, which is a goal among the third goals, or intermediate goals may be set as one or more consecutive goals including the fourth goal, and then, finally, the first goal, which is an ideal goal, may be set.

[0103] As described above, the information processing device 11 in the information processing system 1 according to this embodiment outputs advice for a specified goal regarding exercise for the subject 41, and then evaluates the motivation of the subject 41, and based on the results of the evaluation, outputs advice different from the advice, thereby making it possible to provide advice appropriate to the motivation of the subject 41.

[0104] For example, in the case where advice is generated for a user based only on the level of proficiency as in the conventional technology, if the user is unable to put the advice into practice and the goal does not change, the same advice may continue to be generated. In this way, in the conventional technology, if the user continues to be unable to put the same advice into practice, the user's motivation may decrease, making it difficult to achieve the goal.

[0105] In contrast, in the information processing device 11 according to this embodiment, the advice presented regarding the goal can be changed to different advice that corresponds to the motivation of the subject 41, depending on the evaluation result of the motivation of the subject 41, and then presented. As a result, the information processing device 11 according to the present embodiment can prevent a decrease in the motivation of the user, and can maintain or improve the motivation of the user.

[0106] For example, in the information processing device 11 according to this embodiment, the motivation of the subject 41 who is the target of instruction can be estimated based on information on the exercise and behavior of the subject 41, and advice can be provided by setting an intermediate goal of a difficulty level that is easy for the subject 41 to achieve according to the estimated motivation. As a result, the information processing device 11 according to this embodiment can support the subject 41 in exercising without straining himself / herself while always maintaining motivation to achieve each goal, and can encourage the subject 41 to proactively engage in exercise and take on the challenge of achieving the goal.

[0107] As an example of configuration, the information processing device 11 includes a goal setting unit 115, an advice generating unit 116, an output unit 117, a motivation estimating unit 113, and an evaluation unit 114. The goal setting unit 115 sets a first goal for the exercise of the subject 41. The first goal is an ideal goal. The advice generator 116 generates a first advice for the first goal. The output unit 117 outputs the first goal and the first advice. The motivation estimation unit 113 estimates the motivation of the subject 41. The evaluation unit 114 evaluates the motivation of the subject 41 toward the first goal. The advice generating unit 116 generates second advice different from the first advice based on the evaluation result of the evaluating unit 114. The output unit 117 outputs the second advice. Therefore, the information processing device 11 can present the second advice based on the evaluation result of the motivation of the subject 41 for the first goal to the subject 41, and can provide advice suitable for the motivation of the subject 41.

[0108] As one configuration example, the information processing device 11 includes an exercise information acquisition unit 111. The exercise information acquisition section 111 acquires information related to the exercise of the subject 41 from a sensor attached to the subject 41. In this embodiment, the sensor is a sensor of the sensor section 21. The goal setting unit 115 sets a first goal based on information regarding the exercise of the subject 41. Therefore, in the information processing device 11, a goal suitable for the athletic ability or the like of the subject 41 can be set as the first goal.

[0109] As one configuration example, in the information processing device 11, the motivation estimation section 113 estimates the motivation of the subject 41 based on information related to the exercise of the subject 41. Therefore, the information processing device 11 can estimate the motivation of the subject 41, reflecting the actual exercise status of the subject 41.

[0110] As one configuration example, in the information processing device 11, the motivation estimation unit 113 estimates the motivation of the subject 41 based on the information regarding the subject 41's exercise, such as the time the subject 41 exercised, the number of times the subject 41 exercised, and the exercise intensity when the subject 41 exercised. Therefore, the information processing device 11 can estimate the motivation of the subject 41, reflecting the exercise time, the number of times of exercise, and the exercise intensity. In addition, exercise frequency may be used together with or instead of the number of times of exercise.

[0111] As one configuration example, in the information processing device 11, the motivation estimation section 113 estimates the motivation of the target person 41 based on the number of times the target person 41 has viewed the first goal and the first advice output to the external device. Therefore, the information processing device 11 can estimate the motivation of the subject 41 based on the behavior of the subject 41, such as viewing advice, etc. Here, it is usually estimated that the greater the number of views, the higher the motivation. In this embodiment, the display device 31 is an example of an external device.

[0112] As one configuration example, in the information processing device 11, the goal setting unit 115 sets a second goal different from the first goal based on the evaluation result. The second goal is an intermediate goal, and in this case, is the first intermediate goal. The second advice is advice for the second goal. Therefore, in the information processing device 11, by setting an intermediate goal that is a goal at an intermediate stage before reaching the ideal goal, it is possible to prevent the subject 41 from giving up on the exercise midway.

[0113] As one configuration example, the information processing device 11 includes a determination unit 112 . The determination unit 112 determines the deviation between the current state of the subject 41 and the state defined by the first goal. The goal setting unit 115 sets a second goal based on the result of evaluation by the evaluation unit 114 based on the motivation of the subject 41 and the determination result of the determination unit 112. Therefore, in the information processing device 11, for example, an intermediate goal can be set that reflects the level of motivation of the subject 41 and the discrepancy between the current state of the subject 41 and the ideal target state.

[0114] As one configuration example, in the information processing device 11, the goal setting unit 115 sets the level of the second goal, which is set when the motivation estimation unit 113 estimates that the motivation of the subject 41 is high, to a level closer to the level of the first goal than the level of the second goal, which is set when the motivation estimation unit 113 estimates that the motivation of the subject 41 is low. Therefore, in the information processing device 11, when the subject 41 is highly motivated, it is possible to set an intermediate goal that is closer to the ideal goal than when the subject 41 is less motivated. In other words, it is estimated that the subject 41 who is highly motivated is more likely to achieve a higher intermediate goal. The level of motivation of the subject 41 does not necessarily have to be determined as a continuous value, but may be determined as a discrete value such as high, medium, or low.

[0115] As one configuration example, in the information processing device 11, the determination unit 112 determines, from information on the exercise of the subject 41, whether the current state of the subject 41 has achieved the second goal state. The motivation estimation unit 113 estimates the motivation of the target person 41 based on the period of time it takes for the target person 41 to achieve the second goal. The evaluation unit 114 evaluates the motivation of the subject 41 toward the second goal. The goal setting unit 115 sets a third goal different from the second goal based on the result of the motivation evaluation by the evaluation unit 114. The third goal is an intermediate goal, and in this case, is the second intermediate goal. Therefore, the information processing device 11 can set a second intermediate goal that reflects the motivation of the subject 41 toward the first intermediate goal, thereby allowing intermediate goals suitable for the motivation of the subject 41 to be set sequentially.

[0116] Here, in this embodiment, a case has been shown in which one or more intermediate goals are set by the goal setting unit 115, but intermediate goals do not necessarily have to be set. For example, in the information processing device 11, only the ideal goal may be set, and acquisition of exercise information, various judgments, estimation of motivation, evaluation, generation and output of advice, etc. may be performed.

[0117] In addition, in the information processing device 11 according to this embodiment, for example, the exercise information acquisition unit 111, the judgment unit 112, the motivation estimation unit 113, the evaluation unit 114, the goal setting unit 115, the advice generation unit 116, etc. may use a configuration that performs processing using machine learning, or may use a configuration that performs processing using parameters such as predetermined arithmetic expressions and thresholds without using machine learning.

[0118] In this embodiment, the subject 41's movement to play a sport or the like has been described using the term "exercise," but for example, the subject 41's performing a specific type of exercise to achieve an ideal goal of the exercise may be called practice, etc. Here, the specific type of exercise may be, for example, a specific sporting exercise, or an exercise that moves a specific body part in a specific manner. In this case, the exercise information, exercise-related information, exercise time, number of exercises, exercise frequency, exercise intensity, and exercise load in this embodiment may be referred to as practice information, practice-related information, practice time, number of exercises, practice frequency, practice intensity, and practice load, respectively, for example.

[0119] A program for implementing the functions of any of the components of any of the above-described devices may be recorded in a computer-readable recording medium, and the program may be read into a computer system and executed. The term "computer system" as used herein includes hardware such as an operating system or peripheral devices. The term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs (Read Only Memory), and CDs (Compact Discs)-ROMs, and storage devices such as hard disks built into computer systems. The term "computer-readable recording medium" also refers to storage devices that hold a program for a certain period of time, such as volatile memory in a computer system that is a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. The volatile memory may be a RAM. The recording medium may be a non-transitory recording medium.

[0120] The above program may be transmitted from a computer system in which the program is stored in a storage device or the like to another computer system via a transmission medium, or by transmission waves in the transmission medium. The "transmission medium" that transmits the program refers to a medium that has the function of transmitting information, such as a network such as the Internet or a communication line such as a telephone line. The above program may be for realizing a part of the above-mentioned functions. The above program may be a so-called differential file that can realize the above-mentioned functions in combination with a program already recorded in the computer system. The differential file may be called a differential program.

[0121] The function of any of the components in any of the above-described devices may be realized by a processor. Each process in the embodiment may be realized by a processor that operates based on information such as a program and a computer-readable recording medium that stores information such as a program. The functions of each part of the processor may be realized by individual hardware, or the functions of each part may be realized by integrated hardware. The processor includes hardware, and the hardware may include at least one of a circuit that processes digital signals and a circuit that processes analog signals. The processor may be configured using one or more circuit devices mounted on a circuit board, or one or both of one or more circuit elements. An IC (Integrated Circuit) or the like may be used as the circuit device, and a resistor or a capacitor or the like may be used as the circuit element.

[0122] The processor may be a CPU. However, the processor is not limited to a CPU, and various processors such as a GPU (Graphics Processing Unit) or a DSP (Digital Signal Processor) may be used. The processor may be a hardware circuit using an ASIC (Application Specific Integrated Circuit). The processor may be configured with multiple CPUs, or may be configured with a hardware circuit using multiple ASICs. The processor may be configured with a combination of multiple CPUs and a hardware circuit using multiple ASICs. The processor may include one or more of an amplifier circuit or a filter circuit that processes an analog signal.

[0123] Although the embodiments have been described above in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and designs that do not deviate from the gist of this disclosure are also included.

[0124] [Note] Below, <Configuration Example 1> to <Configuration Example 10> are shown. In addition, the lower configuration example may or may not be applied to the higher configuration example. Furthermore, a lower configuration example that is applicable to any of the two or more higher configuration examples may be applied to any of the two or more higher configuration examples, i.e., two or more application examples are generated, and a configuration example that is even lower than the lower configuration example may be applied to any of these two or more application examples.

[0125] <Configuration example 1> A goal setting unit that sets a first goal for exercise of the subject; an advice generator that generates a first advice for the first goal; an output unit that outputs the first goal and the first advice; A motivation estimation unit that estimates the motivation of the subject; An evaluation unit that evaluates the motivation of the subject with respect to the first goal, the advice generation unit generates second advice different from the first advice based on an evaluation result of the evaluation unit; The output unit outputs the second advice. Information processing device.

[0126] <Configuration example 2> an exercise information acquisition unit that acquires information regarding the exercise of the subject from a sensor attached to the subject; The goal setting unit sets the first goal based on information about the exercise of the subject. The information processing device described in <Configuration Example 1>.

[0127] <Configuration example 3> an exercise information acquisition unit that acquires information regarding the exercise of the subject from a sensor attached to the subject; The motivation estimation unit estimates the motivation of the subject based on information regarding the exercise of the subject. The information processing device described in <Configuration Example 1>.

[0128] <Configuration example 3A> <Configuration Example 2> and <Configuration Example 3> may be combined. In this case, the exercise information acquisition unit in <Configuration example 2> and the exercise information acquisition unit in <Configuration example 3> may be a common component.

[0129] <Configuration Example 4> The motivation estimation unit estimates the motivation of the subject based on a time during which the subject exercised, a number of times the subject exercised, and an exercise intensity when the subject exercised, which are included in information regarding the exercise of the subject. The information processing device according to <Configuration Example 3> or <Configuration Example 3A>.

[0130] <Configuration Example 5> The motivation estimation unit estimates the motivation of the subject based on the number of times the subject has viewed the first goal and the first advice outputted to an external device. The information processing device according to any one of <Configuration Example 1> to <Configuration Example 4> and <Configuration Example 3A>.

[0131] <Configuration Example 6> the goal setting unit sets a second goal different from the first goal based on the evaluation result; The second advice is advice for the second goal. The information processing device according to any one of <Configuration Example 1> to <Configuration Example 5> and <Configuration Example 3A>.

[0132] <Configuration Example 7> a determination unit that determines a deviation between a current state of the subject and a state defined by the first goal; The goal setting unit sets the second goal based on a result of evaluation by the evaluation unit based on the motivation of the subject and the judgment result of the judgment unit. The information processing device according to <Configuration Example 6>.

[0133] <Configuration Example 8> the goal setting unit sets a level of the second goal, which is set when the motivation estimation unit estimates that the motivation of the subject is high, to a level closer to the level of the first goal than a level of the second goal, which is set when the motivation estimation unit estimates that the motivation of the subject is low. The information processing device according to <Configuration Example 6> or <Configuration Example 7>.

[0134] <Configuration Example 9> The determination unit determines whether the current state of the subject has achieved the second goal state based on information about the subject's movement; The motivation estimation unit estimates the motivation of the subject based on a period of time it takes for the subject to achieve the second goal; The evaluation unit evaluates the subject's motivation toward the second goal, The goal setting unit sets a third goal different from the second goal based on a result of the motivation evaluation by the evaluation unit. The information processing device described in <Configuration Example 7>.

[0135] <Configuration example 9A> The contents described in <Configuration Example 8> may be combined with <Configuration Example 9>.

[0136] It is also possible to provide a program recording medium for recording a program executed by the processor in the information processing device as described above. <Configuration Example 10> A program recording medium for recording a program, The program includes: a first goal setting function for setting a first goal for the subject's exercise; a first advice generating function for generating a first advice for the first goal; a first output function for outputting the first goal and the first advice; A first estimation function for estimating the motivation of the subject; A first evaluation function for evaluating the subject's motivation toward the first goal; a second advice generating function that generates a second advice different from the first advice based on an evaluation result of the first evaluation function; A second output function for outputting the second advice; To achieve this, Program recording medium. [Explanation of symbols]

[0137] 1...information processing system, 11...information processing device, 21...sensor unit, 31...display device, 41...subject, 111...exercise information acquisition unit, 112...judgment unit, 113...motivation estimation unit, 114...evaluation unit, 115...goal setting unit, 116...advice generation unit, 117...output unit, 118...storage unit, T1...table

Claims

1. a goal setting unit that sets a first goal for the subject's exercise; an advice generator that generates a first advice for the first goal; an output unit that outputs the first goal and the first advice; A motivation estimation unit that estimates the motivation of the subject; An evaluation unit that evaluates the motivation of the subject with respect to the first goal, the advice generating unit generates second advice different from the first advice based on an evaluation result of the evaluating unit; The output unit outputs the second advice. Information processing device.

2. an exercise information acquisition unit that acquires information regarding the exercise of the subject from a sensor attached to the subject; The goal setting unit sets the first goal based on information regarding the exercise of the subject. The information processing device according to claim 1 .

3. an exercise information acquisition unit that acquires information regarding the exercise of the subject from a sensor attached to the subject; The motivation estimation unit estimates the motivation of the subject based on information regarding the exercise of the subject. The information processing device according to claim 1 .

4. The motivation estimation unit estimates the motivation of the subject based on a time during which the subject exercised, a number of times the subject exercised, and an exercise intensity when the subject exercised, which are included in information regarding the exercise of the subject. The information processing device according to claim 3 .

5. The motivation estimation unit estimates the motivation of the subject based on the number of times the subject has viewed the first goal and the first advice outputted to an external device. The information processing device according to claim 4.

6. The goal setting unit sets a second goal different from the first goal based on the evaluation result, The second advice is advice for the second goal. The information processing device according to claim 1 .

7. A determination unit that determines a deviation between a current state of the subject and a state defined by the first goal, The goal setting unit sets the second goal based on a result of evaluation by the evaluation unit based on the motivation of the subject and the judgment result of the judgment unit. The information processing device according to claim 6.

8. the goal setting unit sets a level of the second goal, which is set when the motivation estimation unit estimates that the motivation of the subject is high, to a level closer to a level of the first goal than a level of the second goal, which is set when the motivation estimation unit estimates that the motivation of the subject is low. The information processing device according to claim 7.

9. The determination unit determines whether the current state of the subject has achieved the second goal state based on information about the subject's movement; The motivation estimation unit estimates the motivation of the subject based on a period of time it takes for the subject to achieve the second goal; The evaluation unit evaluates the motivation of the subject with respect to the second goal, The goal setting unit sets a third goal different from the second goal based on a result of the motivation evaluation by the evaluation unit. The information processing device according to claim 7.

10. A program recording medium for recording a program, The program includes: A first goal setting function for setting a first goal for the subject's exercise; a first advice generating function for generating a first advice for the first goal; a first output function for outputting the first goal and the first advice; A first estimation function for estimating the motivation of the subject; A first evaluation function for evaluating the subject's motivation toward the first goal; a second advice generating function that generates a second advice different from the first advice based on an evaluation result of the first evaluation function; a second output function for outputting the second advice; To achieve this, Program recording medium.

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