Information processing device, exercise motivation generating method, and exercise motivation generating program

Abstract

To provide an information processing device, an exercise motivation creation method, and an exercise motivation creation program capable of creating exercise motivation of an exerciser and causing him or her to keep the exercise motivation.SOLUTION: A target attainment cost calculation device 10 sets target body shape data indicating a body shape that a user targets at, and on the basis of measured body data on the user, estimates future body shape data indicating a body shape of the user after a lapse of a predetermined period. The target attainment cost calculation device 10 calculates costs required for reaching the target body shape data from the estimated future body shape data, and displays it on a display unit.SELECTED DRAWING: Figure 9

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an exercise motivation generating method, and an exercise motivation generating program. [Background technology]

[0002] In recent years, sports gyms (also known as training gyms or fitness clubs) have become widespread, and an increasing number of people are exercising to maintain their health and physique. As a result, many exercisers want to know the effect their training has on their physique.

[0003] For example, in order to predict in advance the effects of continuing moderate physical activity (exercise), Patent Document 1 discloses a body shape change prediction device that calculates subcutaneous fat thickness before and after prediction based on data selected from an individual's current personal parameters such as height, weight, age, and sex and activity data indicating the individual's activity level, and converts the subcutaneous fat thickness before and after prediction into cheek subcutaneous fat thickness to calculate changes in facial contour before and after prediction.

[0004] Patent Document 2 also discloses a health information service system that extracts time series patterns in which a user's health and beauty condition changes or time series patterns in which the user's health and beauty condition does not change based on time series data of health and beauty measurement information related to the user's past health and beauty, extracts a first health and beauty behavior that the user did not perform when the time series pattern applies during a period in which the user did not perform a health and beauty behavior based on the user's behavioral history, and generates effectiveness evaluation information for the non-performance of the first health and beauty behavior using each health and beauty measurement information during the non-performance period. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-48649 [Patent Document 2] Japanese Patent Application Publication No. 2018-110013 Summary of the Invention [Problem to be solved by the invention]

[0006] The device described in Patent Document 1 allows exercisers to check changes in facial contours based on their personal activity level, while the system described in Patent Document 2 allows users to check the effects of not performing health and beauty behaviors.

[0007] However, even if the effects of performing or not performing training are confirmed using an information processing device, it is predictable that many people will approach their ideal body shape if they train, and will not achieve their ideal body shape if they do not train.

[0008] For this reason, even for gym users, simply checking the effects of the training they are about to do is not enough to motivate them to continue training, and as a result, they may not be able to continue exercising continuously, and may not achieve their desired body shape, or even if they do achieve their desired body shape, they may not be able to maintain it.

[0009] Therefore, an object of the present invention is to provide an information processing device, a method for generating exercise motivation, and a program for generating exercise motivation, which are capable of generating and maintaining an exerciser's motivation to exercise. [Means for solving the problem]

[0010] An information processing device according to one aspect of the present invention includes a setting unit for setting target physical data indicating a target body shape, and a cost calculation unit for calculating a cost required for the subject to reach the target body shape based on the measured physical data and the target physical data of the subject. This configuration allows the subject, who is an exerciser, to recognize the cost required to reach the target body shape, weight, body composition, etc., thereby generating and maintaining the exerciser's motivation to exercise.

[0011] The information processing device may further include an estimation unit that estimates future physical data representing the subject's physical state after a predetermined period based on the measured physical data of the subject, and the cost calculation unit calculates a cost required to reach the target physical data from the future physical data estimated by the estimation unit. With this configuration, the subject can be made aware of the cost corresponding to the time when he or she will start exercising, based on future changes in the subject's body.

[0012] In the information processing device, the cost calculation means may calculate a level of strain required by the subject to reach the target body using a difference between the subject's physical data at an arbitrary time point and the target physical data and a period from the arbitrary time point to the time when the subject reaches the target body, and calculate the cost based on the level of strain. With this configuration, the cost of the subject is calculated based on the level of strain required by the subject to reach the target body, allowing for more accurate cost calculation. Note that the arbitrary time point may be the present time or a future time point. The subject's physical data may be previously measured physical data or future physical data.

[0013] In the information processing device, the body may be the body shape of the subject, and an image showing the body shape of the subject after the predetermined period has elapsed and a target body shape estimated by the estimation means may be displayed on a display means. With this configuration, it is possible to more easily recognize the future body of the subject.

[0014] In the information processing device, the cost calculation means may calculate the cost based on the measured physical data of the subject, the target physical data, and the amount of change in the subject's body according to the amount of exercise of the subject. With this configuration, the cost required for the subject to achieve the target body shape can be calculated more accurately.

[0015] In the information processing device, the cost may be at least one of the amount of money, time, and amount of exercise required by the subject to reach the target body, and information indicating the state of the exercise performed to reach the target body. With this configuration, the subject can be made to specifically recognize the cost.

[0016] The information processing device may further include a comparison unit that compares the physical data representing the subject's body with the target physical data, and a notification unit that notifies the subject when the physical data reaches the target physical data. With this configuration, the subject can be made aware that their body has reached the target body.

[0017] One embodiment of the present invention provides a method for generating motivation to exercise, which includes a first step of setting target physical data indicating a target body shape, and a second step of calculating the cost required for the subject to reach the target body shape based on the subject's measured physical data and the target physical data.

[0018] One embodiment of the exercise motivation creation program of the present invention causes a computer to function as a setting means for setting target physical data indicating a target body, and a cost calculation means for calculating the cost required by the subject to reach the target body based on the subject's measured physical data and the target physical data. [Effects of the Invention]

[0019] According to the present invention, it is possible to generate motivation for exercise in an exerciser and maintain that motivation. [Brief explanation of the drawings]

[0020] [Figure 1] FIG. 1 is a schematic diagram of a cost-to-target calculation device according to this embodiment. [Figure 2] FIG. 2 is a functional block diagram showing the configuration of the cost-to-target calculation function of this embodiment. [Figure 3] FIG. 3 is a schematic diagram showing the relationship between the current body shape and the target body shape. [Figure 4] FIG. 4 is a diagram for explaining the function for calculating the cost, where (A) is the user's exercise plan, (B) is the amount the user will pay, and (C) is the user's exercise period. [Figure 5] FIG. 5 is a schematic diagram showing the relationship between the current body shape, future body shape, and target body shape in the case where no action is started from the present time. [Figure 6] FIG. 6 is a schematic diagram showing the relationship between the current body shape, future body shape, and target body shape when an action is started from the present time. [Figure 7] FIG. 7 is a schematic diagram used to explain the estimation of the future body shape in this embodiment. [Figure 8] FIG. 8 is a schematic diagram showing changes in the actual body shape and estimated body shape of the user in this embodiment. [Figure 9] FIG. 9 is a flowchart showing the flow of the cost-to-target calculation process of this embodiment. [Figure 10] FIG. 10 is a flowchart showing the flow of a cost-to-target calculation process according to another embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0021] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Note that the embodiment described below shows an example of how the present invention is implemented, and the present invention is not limited to the specific configuration described below. When implementing the present invention, a specific configuration according to the embodiment may be appropriately adopted. In this embodiment, the information processing device of the present invention is described as an independent device, such as a cost-to-target calculation device, as an example, but is not limited to this, and the information processing device of the present invention may be incorporated into other devices such as a body composition monitor. Furthermore, the mathematical formulas described in the embodiment are also examples, and are not limited to these.

[0022] FIG. 1 is a schematic diagram of a cost-to-achieve calculation device 10 according to this embodiment. The cost-to-achieve calculation device 10 according to this embodiment is an information processing device that sets target physical data indicating a target physical shape, and calculates the cost required for a user to reach the target physical shape based on the subject's measured physical data and the target physical data. The cost-to-achieve calculation device 10 according to this embodiment is, for example, a desktop or laptop personal computer, a tablet terminal device, or the like. In the following description, the subject is referred to as the user, and the measured physical data is referred to as measured physical data.

[0023] Furthermore, the term "body" refers to a person's body shape, weight, body composition, etc., and in this embodiment, the target body is described as a body shape as an example. That is, the cost-to-go-to-go calculation device 10 of this embodiment calculates, as an example, the cost required for the user to achieve the target body shape. As will be described in detail later, the user's body shape is calculated (estimated) based on the user's measured height, weight, and body composition.

[0024] Body composition is biological information acquired by a body composition monitor. The body composition monitor is equipped with a load cell for measuring the weight of the person (user) being measured and electrodes for measuring the bioimpedance of the person being measured. The body composition monitor then calculates the body composition of the whole body and each body part by applying the registered information of the person being measured (age, sex, height), weight, and each bioimpedance to a predetermined regression equation. Body composition includes fat percentage, fat mass, lean mass, muscle mass, visceral fat mass, visceral fat level, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, total body water percentage, BMI, intracellular fluid volume, and extracellular fluid volume. The measured bioimpedance itself may be treated as body composition.

[0025] Furthermore, cost refers to expenses, labor, time, and mental or physical burden, and more specifically, is a collective term for the amount of money, time (exercise period), and amount of exercise (exercise plan) required for a user to reach a target physique (target body shape). Furthermore, if a user has previously trained to reach a similar target body shape and has stored information (image data or diary data) showing the training, this information may be shown to the user as cost. This allows the user to specifically recognize the cost of reaching the target body shape.

[0026] As an example, the cost-to-goal calculation device 10 is installed in a training gym. For example, an instructor (trainer) at the training gym asks a user who is a member of the training gym about a target body shape, and causes the cost-to-goal calculation device 10 to calculate the cost required to reach that target body shape. The instructor then explains the calculated cost to the user and encourages them to train. Details of cost calculation will be described later, but in this embodiment, the cost is calculated using the time period between any two points, physical data, and the difference. Additionally, costs may be calculated using body shape change estimates calculated from historical data of the user's body composition.

[0027] As shown in FIG. 1, the cost-to-target calculation device 10 includes a main control unit 12, a main memory unit 14, an auxiliary memory unit 16, a display 18, an operation unit 20, and a communication unit 22.

[0028] The main control unit 12 is, for example, a CPU (Central Processing Unit) or the like, and controls the operation of the cost-to-reach calculation device 10 .

[0029] The main memory unit 14 is, for example, a RAM (Random Access Memory) or a DRAM (Dynamic Random Access Memory), and is used as a work area when the main control unit 12 executes processes based on various programs, a memory area for temporarily storing data, etc.

[0030] The auxiliary storage unit 16 is, for example, a non-volatile memory such as a flash memory or an HDD (Hard Disk Drive), and stores various data and programs used for processing by the main control unit 12. The programs stored in the auxiliary storage unit 16 include, for example, the OS (Operating System) of the cost to reach target calculation device 10, various drivers for controlling various hardware, and software for executing the cost to reach target calculation function of this embodiment.

[0031] The auxiliary storage unit 16 stores a body shape database that associates multiple pieces of physical data (height data, weight data, body composition data) with body shape data, and data such as the body composition of each user measured by a body composition monitor and the user's registered information (age, sex, height). Note that these data may not be stored in the auxiliary storage unit 16, but may be stored in another information processing device such as a server that can send and receive data via the communication unit 22.

[0032] The display 18 is, for example, an LCD (Liquid Crystal Display) or the like, and displays images based on processing by the main control unit 12. The operation unit 20 is used to perform various input operations on the cost-to-target calculation device 10, and is, for example, a touch panel, a keyboard, a mouse, a touch pad, buttons, etc.

[0033] The communication unit 22 transmits and receives various data to and from the body composition monitor, other information processing devices, and the like.

[0034] The main control unit 12, main memory unit 14, auxiliary memory unit 16, display 18, operation unit 20, and communication unit 22 are electrically connected to one another via a system bus 24. Therefore, the main control unit 12 accesses the main memory unit 14 and auxiliary memory unit 16, displays images on the display 18, grasps the operation status of the operation unit 20, and accesses the body composition monitor and other information processing devices via the communication unit 22.

[0035] Fig. 2 is a functional block diagram relating to the cost to reach goal calculation function of this embodiment. As an example, the functions shown in Fig. 2 are executed by the main control unit 12 of the cost to reach goal calculation device 10 when a program is started. However, this is not limiting, and when the cost to reach goal calculation device 10 is provided in a body composition monitor or the like, the functions shown in Fig. 2 may be realized by individual hardware such as an ASIC (Application Specific Integrated Circuit).

[0036] The cost-to-go-to-go calculation device 10 includes an image processing control unit 30, a target body shape setting unit 32, a body shape estimation unit 34, a change amount estimation unit 36, a cost calculation unit 38, a body shape data comparison unit 40, and a notification processing unit 42.

[0037] The image processing control unit 30 controls the display 18 to display an image based on the image data.

[0038] The target body shape setting unit 32 sets target body shape data indicating a target body shape for the user. In this embodiment, along with setting the target body shape data, the time when the user wishes to reach the target body shape (hereinafter referred to as "time when the target body shape is reached") can also be set. Note that, as will be described later, if the exercise period is included in the cost, the time when the target body shape is reached does not need to be set.

[0039] The user's target body shape and other information are input by the user, who is a member of the training gym, or the instructor via the operation unit 20 while referring to the image displayed on the display 18. More specifically, for example, a plurality of different body shapes according to the user's age, height, and gender are displayed on the display 18, and one of the plurality of body shapes is selected, and the selected body shape is set as target body shape data in association with the user's registered information. The target body shape data selected by the user is extracted from a body shape database stored in the auxiliary storage unit 16.

[0040] The target body shape data is also associated with various data indicating body composition and weight corresponding to the body shape, as well as sizes such as leg circumference, waist circumference, chest circumference, and arm circumference.

[0041] The target body shape data set in the target body shape setting unit 32 may be, for example, standard body shape data statistically determined according to the ages, heights, and sexes of multiple people. In other words, if the user's current body shape differs from the standard body shape due to obesity or the like, the target body shape data may be automatically set based on the user's registered information, rather than the user or instructor arbitrarily inputting the target body shape.

[0042] The body shape estimation unit 34 estimates future body shape data indicating the body shape of the user after a predetermined period of time has passed, based on the measured physical data of the user. Details of the estimation of future body shape data by the body shape estimation unit 34 will be described later.

[0043] The change amount estimating unit 36 ​​calculates the amount of change in the body according to the amount of exercise of the user over a predetermined period (hereinafter referred to as "body shape change estimate"). The calculation of the body shape change estimate by the change amount estimating unit 36 ​​will be described in detail later.

[0044] The cost calculation unit 38 calculates the cost required for the user to reach the target body shape based on the body shape data based on the user's measured physical data and the target body shape data. Note that the cost calculation unit 38 of this embodiment calculates the cost required to reach the target body shape data from the future body shape data estimated by the body shape estimation unit 34. Details of the calculation of the cost by the cost calculation unit 38 will be described later.

[0045] The body shape data comparison unit 40 compares the current body shape data indicating the user's current body shape with the target body shape data, and determines whether the difference between the current body shape data and the target body shape data is within a predetermined range. In other words, if the difference between the current body shape data and the target body shape data is within the predetermined range, the user's body shape has reached the target body shape.

[0046] Whether the user's body shape has reached the target body shape is determined, for example, by whether the average value of the differences between the sizes of the leg circumference, waist circumference, chest circumference, and arm circumference, etc., derived from the current body shape data and the sizes of the target body shape data is within a predetermined range. Alternatively, without being limited to this, it may be determined by whether one or more sizes or weight that the user considers important is within a predetermined range.

[0047] The notification processor 42 performs notification processing when the current body shape data reaches the target body shape data. For example, the notification processing may display an image on the display 18 or a pre-registered user's mobile terminal device indicating that the current body shape data has reached the target body shape data. The notification processor 42 may also display the difference between the current body shape data and the target body shape data calculated by the body shape data comparator 40 on the display 18 or the like, allowing the user to recognize the degree to which the target body shape has been achieved.

[0048] Alternatively, the present invention is not limited to the above, and the body shape data comparison unit 40 may determine whether the difference between the current body shape data and the target body shape data has exceeded a predetermined value, and the notification processing unit 42 may issue a notification if the difference has exceeded the predetermined value. In this manner, the body shape data comparison unit 40 may compare the current body shape data with the target body shape data based on other criteria, and the notification processing unit 42 may issue a notification.

[0049] Next, calculation of the cost by cost calculation unit 38 will be described with reference to Fig. 3 to Fig. 6. In this embodiment, the cost is calculated using the period from the present time or any future time point to the time point at which the user reaches the target body shape (target time point) and the difference in the user's physical data at these times.

[0050] 3 is a schematic diagram showing the relationship between the user's current body shape, future body shape, and target body shape. The vertical axis of FIG. 3 represents the user's body shape, in other words, the degree of obesity, and the horizontal axis of FIG. 3 corresponds to time.

[0051] Points A1, A2, and A3 in Figure 3 indicate the user's body shape at past times T1, T2, and T3 (hereinafter referred to as "past body shape") based on the user's weight and body composition measurements, and point A4 indicates the user's body shape at the current time Tnow (hereinafter referred to as "current body shape").

[0052] Point G indicates a target body shape Cg that the user aims for. The target body shape may be, for example, one arbitrarily set by the user or a standard body shape according to the user's age, height, sex, etc.

[0053] That is, Figure 4 is a diagram visually showing the cost L for a user to reach a target body shape Cg when the user starts an action from the current time Tnow. Note that an action is a general term for various trainings, exercises, etc. that the user performs to reach the target body shape.

[0054] Here, the following formulas (1) and (2) are formulas for calculating the cost L. I is the user's level of burden (or load), and indicates the amount of burden (load) per unit period, such as one month or one week. Furthermore, t indicates a predetermined period (the user's exercise period).

[0055]

number

[0056] The burden level l is calculated, for example, based on the amount of change in body shape and the time required for this body shape change. The amount of change in body shape is, for example, the difference between the current body shape Cnow and the target body shape Cg. The time required for body shape change is, for example, the time Tg-Tnow from the current time Tnow, which is the current body shape Cnow, to the target time Tg, which is the time required for the target body shape Cg. From these, the burden level l can be expressed, for example, by the following equation (3).

number

[0057] For example, if the target time Tg is two months from the current time Tnow and the difference between the current body shape Cnow and the target body shape Cg is 5 kg, the burden level 1 is 2.5 kg / month.

[0058] The burden level l may be calculated by multiplying or dividing the equation (3) by a coefficient, or by adding or subtracting a constant, or by using a formula different from the above equation (3). Furthermore, the cost L may be corrected using an estimated body shape change p, the details of which will be described later, as in the following equation (4).

number

[0059] Furthermore, the function f is a function that can be changed depending on the type of cost L, and may be a proportional function or a step function, as will be described with reference to FIGS. 4(A) to 4(C), for example.

[0060] FIG. 4(A) shows a user's exercise plan, with the horizontal axis representing the user's level of burden l and the vertical axis representing an example of cost L. As shown in FIG. 4(A), the exercise plan changes when the user's level of burden l exceeds a predetermined threshold. Specifically, as shown in the following equation (5), when the level of burden l is between 0 and a predetermined value l1 or less, plan A is selected, and when the level of burden l is above the predetermined value l1 and less than a predetermined value l2, plan B is selected. In other words, the predetermined values ​​l1 and l2 represent the quality of exercise indicated by changes in body shape within a predetermined period.

[0061]

number

[0062] In Figure 4(B), the horizontal axis indicates the user's exercise period, and the vertical axis indicates the amount paid by the user, which is an example of cost L. As shown in Figure 4(B), the amount increases according to the exercise period t. As shown in equations (6) and (7) below, the longer the exercise period t, the lower the unit price (basic fee for the plan, etc.), and the longer the exercise period t, the smaller the rate of increase in the amount. Note that L0 in equation (6) is a conversion coefficient that converts the user's body shape change into an amount of money.

[0063]

number

[0064] Furthermore, without being limited to the example of Figure 4(B), the amount may be calculated based on a function with at least one of the burden level per unit period 1 or the exercise period t as a variable, or the amount may be calculated according to a plan corresponding to burden level 1, or the amount may increase gradually each time the exercise period t exceeds a threshold value.

[0065] In FIG. 4(C), the horizontal axis indicates the amount of change in the user's body shape C0, and the vertical axis indicates the user's exercise period t, which is an example of the cost L. The exercise period t is calculated, for example, as shown in equation (8) below. Note that the burden level l in equation (8) is the amount of change in the body shape per unit period.

[0066]

number

[0067] Line a shown in FIG. 4(C) corresponds to the user's level of strain l1, and line b corresponds to the user's level of strain l2, where l1>12. That is, as shown in FIG. 4(C), for a given user's level of strain l, the exercise period t becomes longer as the user's desired amount of body shape change C0 increases. Also, for a given user's desired amount of body shape change C0, the exercise period t becomes longer as the user's level of strain l increases. However, without being limited to this, the exercise period t may also be calculated using a function in which the amount of body shape change, etc., is treated as a coefficient.

[0068] Figure 5 is a schematic diagram showing the relationship between the current body shape Cnow, the future body shape Cf1 at an arbitrary future time Tf, and the target body shape Cg in the case where the user does not take any action from the current time Tnow and obesity progresses between then and the future time Tf.

[0069] The future body shape Cf1 is estimated based on points A1 to A4 of the past and present body shapes, as will be described in detail later. That is, the example in Fig. 5 visually represents the body shape change to reach the target body shape Cg when the user starts an action at an arbitrary future time Tf (future body shape Cf1) without starting any action from the present time Tnow.

[0070] In the example of Figure 5, if the user starts the action at a future time point Tf, the burden level l is calculated as follows: If the future time point Tf is one month after the current time point Tnow, the future body shape Cf1 weighs 5 kg more than the current body shape A4, the target time point Tg is two months after the current time point Tnow, and the difference between the current body shape Cnow and the target body shape Cg is 5 kg, the burden level l is 10 kg / month.

[0071] On the other hand, FIG. 6 is a schematic diagram showing the relationship between the current body shape Cnow, the future body shape Cf2 at an arbitrary future time point Tf2, and the target body shape Cg when the user starts an action from the current time point Tnow.

[0072] As an example, the future body shape Cf2 is calculated using the following equations (9) and (10). Equations (9) and (10) use the future body shape Cf1 that would occur if no action were taken from the current time Tnow as a reference. Furthermore, α and β in equations (9) and (10) are arbitrary values ​​and may change depending on the type of action and exercise duration starting from the current time Tnow. Note that equation (10) adds the value obtained by multiplying the estimated body shape change p(t) by the value β to the future body shape Cf1, but in the example of Figure 6, the estimated body shape change p(t) is a negative value because the user is taking an action (exercise).

[0073]

number

[0074] In the example of Figure 6, the burden level l is calculated if the user continues the action or starts a different action from the future time point Tf. As an example, if the future time point Tf is one month after the current time point Tnow, the weight of future body shape Cf2 is 1 kg less than that of current body shape A4, the target time point Tg is two months after the current time point Tnow, and the difference between the current body shape Cnow and the target body shape Cg is 5 kg, the burden level l is 4 kg / month.

[0075] 3, 5, and 6, the cost-to-goal calculation device 10 of this embodiment calculates, for example, the cost L from the current body shape Cnow or the future body shapes Cf1, Cf2 to the target body shape Cg. In other words, the slope of the line from the current body shape Cnow or the future body shapes Cf1, Cf2 to the target body shape Cg visually represents the cost L. That is, the greater the slope of the line from the current body shape Cnow or the future body shapes Cf1, Cf2 to the target body shape Cg, the greater the cost L.

[0076] Furthermore, as explained with reference to Figures 5 and 6, the calculation of future body shapes Cf1 and Cf2 includes cases (patterns) where the user takes action from the current time Tnow and where the user takes action, as an example, the estimated change in the user's body shape p is used.

[0077] In this way, the cost calculation unit 38 of this embodiment calculates the level of strain l required by the user to reach the target body using the difference between the user's physical data at any given time and the target physical data, and the period from any given time to the time when the user reaches the target body, and calculates the cost L based on this level of strain l.

[0078] With this configuration, the user's cost L is calculated based on the user's level of strain l to reach their target body shape, allowing for more accurate cost calculation. As mentioned above, the arbitrary time point may be the present time Tnow or a future time point Tf. Furthermore, the user's physical data may be measured physical data (current body shape Cnow) or future physical data (future body shape Cf).

[0079] As a result, the cost-to-goal calculation device 10 of this embodiment allows the user to recognize the cost required to reach the target body shape, thereby generating and maintaining the user's motivation to exercise.

[0080] Next, a description will be given of the estimation of a future body shape by the body shape estimation unit 34. Note that the method of estimating a future body shape described below is an example, and the method is not limited to this.

[0081] In the estimation of the future body shape of this embodiment, body shape data that has a high similarity to future changes in the measured body data of the user is acquired (estimated) as the user's future body shape data in a body shape database.

[0082] The body shape estimation unit 34 of this embodiment estimates the user's future body shape as a body shape change over an arbitrary period of time, for example, by using a vector quantity in which the magnitude of a composite vector of the user's multiple measured body data in multidimensional spatial coordinates represents the period and the direction represents the body shape change. Note that it is preferable to use three or more measured body data points measured on different dates to derive the composite vector.

[0083] Here, Fig. 7 is a diagram showing an example of a body shape database (multidimensional spatial coordinates) used in estimating a future body shape. The example in Fig. 7 shows a three-dimensional coordinate space using height, weight, and body fat percentage as physical data, but if age, height, weight, BMI, and body fat percentage are used as physical data, the space becomes a five-dimensional coordinate space. Furthermore, the cost-to-go-to-target calculation device 10 is not limited to this, and may store a body shape database for each gender, or may store a body shape database that does not distinguish between genders.

[0084] In the example of Figure 7, "◯" (large white circle) represents the user's measured physical data, "·" (small circle) represents physical data contained in the body shape database (hereinafter referred to as "memorized physical data"), and "●" (large black circle) represents memorized physical data that is closest to (similar to) the measured physical data. The dashed line represents the composite vector, and the triangular point represents memorized physical data a predetermined period of time after the present. Corresponding body shape data is associated with the memorized physical data.

[0085] Body shape estimation unit 34 searches for stored physical data that is highly similar to the measured physical data. The similarity is calculated based on the difference between the measured physical data and the stored physical data. Specifically, the similarity is calculated based on the Euclidean distance between the measured physical data and the stored physical data in a multidimensional coordinate space with variables including gender, age, height, weight, BMI, and fat percentage.

[0086] More specifically, a prediction model Ct of the user's physical data calculated from the measured physical data Ct0, Ct1, . . . , Ctn is given by the following equation (11).

[0087]

number

[0088] In equation (11), const is a constant, and a1, a2, ..., an are model parameters that adjust how much Ct-1, Ct-2, ..., Ct-n are reflected in the model. Also, ε is white noise. Note that, for example, if Ct-n is composed of multiple variables (matrix), an is also composed of multiple variables (matrix).

[0089] A further simplification of equation (11) is equation (12) below.

[0090]

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[0091] The prediction model Ct is not limited to the autoregressive model expressed by equations (11) and (12), but may be a moving average model or a model that combines these.

[0092] Based on the prediction model Ct, the body shape estimation unit 34 derives stored body data corresponding to coordinates V(xvj, yvj, zvj) in multidimensional space that have the smallest Euclidean distance from coordinates U(xu, yu, zu) derived as body data at a predetermined time from the present, and acquires body shape data associated with this stored body data as future body shape data. The acquired future body shape data may be changed depending on the degree of similarity between coordinates U(xu, yu, zu) and coordinates V(xvj, yvj, zvj).

[0093] 3, 5, and 6. When calculating future body shape data, the time when the predetermined period has elapsed from the present (the time when the action will start) is input via the operation unit 20. If the input time when the predetermined period has elapsed changes, the estimated future body shape data will naturally change as well.

[0094] FIG. 8 is a schematic diagram showing changes in a user's body shape. In FIG. 8, images for actual weights of 110 kg to 92 kg show body shapes based on measured body data, and arrows indicate the time series. That is, the body shape with an actual weight of 92 kg is the user's current body shape. On the other hand, the image with an estimated weight of 87 kg is an image based on estimated future body shape data.

[0095] 8 may be displayed on the display 18 together with an image showing the user's target body shape and may be used for explanation by the instructor, thereby enabling the user to more easily recognize their current and future body shapes.

[0096] Next, a description will be given of the calculation of the body shape change estimate by the change amount estimating unit 36. Note that the method of calculating the body shape change estimate described below is an example, and the method is not limited to this.

[0097] The estimated body shape change is a value that indicates the potential extent to which a user can change their body composition value over a specified period of time; in other words, it is an index that indicates how easy or difficult it is for an individual user to lose weight. The estimated body shape change may be estimated arbitrarily for the actions (training) performed by the user. For example, if a user performs an action that changes their body composition value by ΔCt over a specified period of time Δt, the estimated body shape change p(t) will be as shown in equation (13) below. As expressed in equation (13), the estimated body shape change p(t) indicates how much the body shape will change over a specified period of time t, and the larger the value of the estimated body shape change p(t), the easier it is for the body shape to change.

[0098]

number

[0099] In equation (13), the estimated change in body shape p(t) changes linearly with respect to time t, but is not limited to this, and the estimated change in body shape p(t) may increase or decrease exponentially or logarithmically with respect to time t.

[0100] An example of calculating the estimated change in body shape p(t) will be described below.

[0101] For example, when calculating an estimated body shape change p(t) based on past data, the body composition values ​​measured during a predetermined period Δt (t0, t1, t2, ..., tn) during which a certain action (training, etc.) is continued are defined as Ct0, Ct1, Ct2, ... Ctn.

[0102] The body composition value may be composed of multiple values ​​such as "body weight, body fat mass, muscle mass," or multiple values ​​may be combined to obtain the estimated body shape change p(t) as a ratio or difference between different body composition values, such as dividing muscle mass by body fat mass or subtracting body fat mass from body weight. Furthermore, the estimated body shape change p(t) is not limited to this, and may also be the difference between body weight, body fat mass, and muscle mass within a predetermined period Δt, or a composite vector.

[0103] Furthermore, the estimated body shape change p(t) may be calculated using the body composition values ​​at the start time t0 of the action and the end time tn or the extreme value Ctext (minimum value Ctmin or maximum value Ctmax) as shown in the following equations (14) and (15). Note that text in the following equations is the time when the extreme value Ctext was obtained.

[0104]

number

[0105]

number

[0106] Furthermore, the estimated body shape change p may be calculated using a discount rate according to the characteristics of the body shape change of the individual user. The discount rate is, for example, the adjustment value shown below, where the adjustment values ​​shown in (1) to (3) below are adjustment values ​​for dividing the above formula (14), and the adjustment value shown in (4) below is an adjustment value for dividing the above formula (15).

[0107] (1) An adjustment value α(Ct0) that takes into account the body composition value at the start of the action t0, such as the tendency for heavier people to lose weight when dieting. (2) An adjustment value β(ΔCt, Δt) that takes into account the fact that the weight loss tendency is large at the start of the diet but gradually decreases over a predetermined period Δt. (3) An adjustment value γ (SD(ΔCt,Δt)) that takes into account variations in changes such as repeated gains and losses of body weight during a specified period Δt. SD is the standard deviation of how closely Ct1 to Ctn-1 follow the function of the change trend represented by the body composition values ​​Ct0 and Ctn for periods t0 and tn. (4) The adjustment value δ(ΔCt_i, ΔCt_j, Δt_i, Δt_j) takes into account the reversal of the trend of change in body composition values ​​at extreme values, such as rebound. ΔCt_i represents the change in body composition values ​​during period Δt_i in interval [0, ext], and ΔCt_j represents the change in body composition values ​​during period Δt_j in interval [ext, n].

[0108] Alternatively, the estimated body shape change p(t) may be calculated based on m different actions pm(t) as shown in the following equation (16).

[0109]

number

[0110] Furthermore, in the body shape change estimate p(t) calculated based on the action, the body shape change estimate for each action pm(t) may be weighted as follows:

[0111] (1) The average value of p1(t)~pm(t). (2) p1(t)~pm(t) is treated as a time series, and actions closer to the present time are given a higher weight so that actions closer to the present time are treated as more reliable. (3) p1(t) to pm(t) are sorted by duration, and the action with the longest duration is weighted higher to treat the action with the longest duration as the most reliable. (4) Treat p(t) as a ranged value based on the standard deviation SD of all actions.

[0112] As another example, the body shape change estimate p(t) may be applied to the prediction model Ct of the user's physical data shown in equation (12) to obtain the following equation (17). γ is a parameter indicating the contribution of the body shape change estimate p(t) to the prediction model Ct. Note that the future body shape of the user who has taken an action may be predicted using any other amount of displacement in the prediction model Ct, not limited to equation (17).

number

[0113] Next, a description will be given of the calculation of costs by the cost calculation unit 38. Note that the cost calculation method described below is an example and is not limited to this.

[0114] The cost calculation unit 38 calculates (derives) the cost, time (exercise period), amount of exercise, etc. required for any given body composition change C. The amount of exercise also corresponds to the degree of difficulty for the user. The calculated cost is displayed on the display 18 so that the user can recognize it.

[0115] When the calculated cost includes the exercise period, the time to reach the target body shape may not be set, and the time to reach the target body shape may be changed depending on the amount of exercise. Even if the time to reach the target body shape is set, the amount of exercise may be calculated as a cost, and the exercise period may be calculated, and the exercise period may be changed depending on the amount of exercise. This allows the user to recognize whether the time to reach the target body shape that they have set is realistic.

[0116] As a specific example, the cost calculation unit 38 calculates the difference between the waist circumference in the future body shape data and the waist circumference in the target body shape data, and calculates the cost required for the user to achieve the waist circumference of the target body shape data based on the waist circumference difference. For example, if the waist circumference difference is 5 cm and a specified training period is set to 3 days to reduce the waist circumference by 1 cm, the exercise period is calculated to be 2 weeks, and if the cost is set to 10,000 yen per month, the cost is calculated to be 5,000 yen. Furthermore, if a time to reach the target body shape is set, the amount of exercise and training menu to be performed from the start of the action until the target body shape is reached are calculated.

[0117] The cost-to-goal calculation device 10 has various data for calculating costs according to body composition changes C stored in the auxiliary storage unit 16. Alternatively, the cost-to-goal calculation device 10 accesses another information processing device (for example, a data server) to acquire various data for calculating costs.

[0118] The cost calculation unit 38 may calculate the cost not only in terms of the amount of money, the exercise period, and the amount of exercise as described above, but also in terms of a numerical value that evokes the user's difficulty. For example, the larger the numerical value calculated by the cost calculation unit 38, the greater the difficulty experienced by the user.

[0119] The cost may also be calculated using the estimated body shape change p(t) as described above. That is, the cost calculation unit 38 may calculate the cost based on the user's measured body data (future body shape data), target body shape data, and the estimated body shape change p(t).

[0120] When calculating costs, if the cost is calculated based only on the difference between future body shape data and target body shape data, body shape changes according to the training content or the characteristics of body shape changes for each individual user are not taken into account. Therefore, by using the body shape change estimate p(t) for each individual user in calculating costs, the characteristics of body shape changes for each individual user are taken into account, and the cost to achieve the user's target body is calculated more accurately.

[0121] The following equation (18) is an example of a calculation formula for cost L using estimated body shape change p(t), and is a modified version of the above equation (4).

[0122]

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[0123] In equation (18), g(p(t)) is a function that converts the estimated body shape change p(t) into cost, and is a function of the same nature as f. Also, g0 is a parameter that indicates how much the estimated body shape change p(t) is reflected in the cost.

[0124] Alternatively, the cost L may be calculated using a similar past body composition change ΔCh and its duration Δh for the same user, as shown in the following equation (19). Δh is the duration of the interval [h0, hn]. Specifically, from a similar past body composition change ΔCh and its duration Δh, a burden level lx is calculated as the burden level l for the similar past body composition change ΔCh, and the burden level lx is used to calculate the cost L. The cost L calculated using equation (19) may also be calculated using the similarity Sc between the burden level l for an arbitrary body composition change C and the burden level lx for the past body composition change ΔCh, as shown in equation (20). In other words, the burden level lx for the past body composition change ΔCh that is most similar to the burden level l for the arbitrary body composition change C based on equation (19) is selected and used for the function f(lx) in equation (20).

[0125] The similarity may be evaluated by, for example, a scalar quantity or Euclidean distance between data, and the similarity may be evaluated using variables such as not only the change in body composition but also the combination of exercise duration, amount, etc. If multiple ΔCh values ​​are obtained, the most recent data or the data with the closest starting body composition value may be used, or the average value of the cost L calculated for each may be used.

[0126]

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[0127] Furthermore, if there is a past body composition change ΔCh of the user that is similar to the user's target body composition change C, and data indicating the actions the user took in the past to achieve the past body composition change ΔCh, as well as the experiences and memories at that time, are stored, these data may be calculated as the cost. Furthermore, if a similar load level l existed in the past, the cost may be the experiences and memories at that time. The experience refers to the content of the action (training menu and amount required), and the memory refers to information such as image data or a diary that shows the state of the past action.

[0128] FIG. 9 is a flowchart showing the flow of the cost-to-reach goal calculation process executed by the cost-to-reach goal calculation device 10. As shown in FIG.

[0129] First, in step 100, the user's current body composition is measured, and the user's current body shape data is acquired (estimated) by the body shape estimation unit .

[0130] In the next step 102, the user's target body shape is input, and the target body shape is set by the target body shape setting unit 32. In step 102, the time period by which the user wishes to reach the target body shape is also set.

[0131] In the next step 104, the estimated body shape change p(t) of the user is calculated by the change amount estimating unit 36. Note that if data for calculating the estimated body shape change p(t) is not stored, the estimated body shape change p(t) does not need to be calculated.

[0132] In the next step 106, the cost calculation unit 38 calculates the cost required to reach the target body shape set in step 102 from the current body shape acquired in step 100.

[0133] In the next step 108, the cost calculation result is displayed on the display 18. This allows the user to recognize the cost required to reach the target body shape from the current body shape, assuming that the current time is the start time of the action.

[0134] In the next step 110, the body shape estimation unit 34 determines whether an instruction to execute estimation of the future body shape has been input, and if the determination is affirmative, proceeds to step 112, and if the determination is negative, terminates the target cost calculation process.

[0135] In step 112, the body shape estimation unit 34 determines whether multiple pieces of measured physical data of the user (for example, three or more pieces) are stored, and if the determination is affirmative, the process proceeds to step 114. On the other hand, if the determination is negative, it is determined that the user's future body shape cannot be estimated, and the cost-to-go calculation process is terminated.

[0136] In the next step 114, the start time of the action is input. The start time of the action is set to a future time (date) that does not include the present.

[0137] In the next step 116, the body shape estimation unit 34 estimates the future body shape of the user at the start of the action.

[0138] In the next step 118, the estimated body shape change p(t) of the user is calculated by the change amount estimating unit 36. Note that if the estimated body shape change p(t) has been calculated in step 104, step 118 does not need to be executed.

[0139] In the next step 120, the cost calculation unit 38 calculates the cost required to reach the target body shape set in step 102 from the future body shape estimated in step 116, taking into account the body shape change estimate p(t).

[0140] In the next step 122, the cost calculation results are displayed on the display 18. This allows the user to recognize the cost from the future body shape at the start of the action to the target body shape. Note that in step 122, the cost calculated in step 106 and multiple costs with different action start times may also be calculated simultaneously on the display 18. This allows the user to recognize the difference in cost due to different action start times.

[0141] In the next step 124, the body shape estimation unit 34 determines whether a change to the start of the action has been input, and if the determination is affirmative, the process returns to step 116. This causes the user's future body shape at the start of the newly input action to be estimated, and the cost required to reach the target body shape from this future body shape is calculated. On the other hand, if the determination is negative, the goal-reaching cost calculation process ends.

[0142] Furthermore, after the user starts an action to reach a target body shape, when the user's measured body data reaches the target body shape data, the fact that the user has reached the target body shape is displayed (notified) on the display 18 or the user's pre-registered mobile terminal device, etc. For this purpose, the cost to reach goal calculation device 10 reads the user's measured body data from a body composition scale that measures the user's measured body data or a server that stores the user's measured body data, etc. Then, the body shape data comparison unit 40 of the cost to reach goal calculation device 10 compares the measured body data with the target body shape data, and when the measured body data reaches the target body shape data, the notification processing unit 42 performs notification processing.

[0143] Although the present invention has been described above using the above-mentioned embodiment, the technical scope of the present invention is not limited to the scope described in the above-mentioned embodiment. Various changes or improvements can be made to the above-mentioned embodiment without departing from the gist of the invention, and such changes or improvements are also included in the technical scope of the present invention.

[0144] For example, in the above embodiment, the future body shape data is calculated based on a composite vector of multiple measured body data, but the present invention is not limited to this. The future body shape data may be calculated by other methods, such as by using an approximation formula for multiple measured body data.

[0145] In the above embodiment, the future body shape data is estimated based on a plurality of measured physical data, but the present invention is not limited to this. The future body shape data may be estimated based on a single measured physical data. For example, the future body shape data may be estimated based on general time-varying physical data corresponding to the user's height, age, and gender, starting from a single measured physical data of the user.

[0146] In the above embodiment, the present invention is described as being used to encourage current gym members to train, but the present invention is not limited to this. For example, the present invention may be used to encourage gym members who have withdrawn from the gym (hereinafter referred to as "former members") to return to the gym (rejoin).

[0147] 10 is a flowchart showing the flow of the cost to reach goal calculation process for the purpose of encouraging reuse, which is executed by the cost to reach goal calculation device 10. Note that, since former members are subjects for whom physical measurement data has been acquired in the past, various information is input into the cost to reach goal calculation device 10 by instructors or office workers at the sports gym. In the following description, former members are also referred to as guidance targets.

[0148] First, in step 200, the current body shape data of the person to be guided is acquired (estimated) by the body shape estimation unit 34. The current body shape data of the person to be guided is estimated based on the progress of body shape changes in the past measured body data of the person to be guided, for example, by reading out from the auxiliary storage unit 16 or the like physical data measured when the person to be guided was attending a sports gym as a member (hereinafter referred to as "past measured body data"). Note that the current body shape data may be estimated using past measured body data when the person to be guided achieved their target body shape or past measured body data when the person to be guided canceled their membership, and the time elapsed since the goal was achieved or the time since the person to be guided canceled their membership.

[0149] Furthermore, the estimation of the present body shape data of the person to be guided in step 200 may use the past estimation result of the future body shape performed when the person to be guided was a member. For example, the present body shape data may be obtained by correcting the past estimation result of the future body shape data of the person to be guided, taking into consideration the measured physical data when the person to be guided achieved the target body shape in the past (for example, the increased muscle mass has increased the basal metabolism and made it easier to burn body fat).

[0150] In the next step 202, the target body shape of the person to be guided is set by the target body shape setting unit 32. Note that since the target body shape desired by the person to be guided is actually unknown, as an example, a target body shape previously set by the person to be guided, or a target body shape that the person to be guided has actually achieved, etc. is set.

[0151] In the next step 204, the change amount estimation unit 36 ​​calculates an estimated change in body shape p(t) for the person to be guided. The estimated change in body shape p(t) is calculated based on actions taken by the person to be guided in the past. Note that if data for calculating the estimated change in body shape p(t) is not stored, the estimated change in body shape p(t) does not need to be calculated.

[0152] In the next step 206, the start time of the action is input. The start time of the action may be the present time, or multiple patterns may be input, such as one month later, two months later, etc.

[0153] In the next step 206, the future body shape of the person to be guided at the start of the action is estimated by the body shape estimation unit 34. As in step 200, the future body shape may be estimated using the past estimation results of the future body shape of the person to be guided. Furthermore, if multiple patterns of action start times are input in step 204, the future body shape of the person to be guided is estimated for each input action start time. Furthermore, if the action start time input in step 204 is the present, the current body shape estimated in step 200 is used as the future body shape.

[0154] In the next step 208, the cost to reach the target body shape set in step 202 from the future body shape estimated in step 206 is calculated by cost calculation unit 38, taking into account the body shape change estimate p(t). The calculated cost is then attached to, for example, a guide to reusing the training gym and sent to the guide recipient.

[0155] 10 makes the target person aware of the cost and motivates them to exercise, thereby increasing the effectiveness of the promotion to reuse. Note that the target person may not only be a former member, but may also be, for example, a current member with an annual contract who has not visited the gym for a predetermined period of time (for example, three months or more). [Explanation of symbols]

[0156] 10. Information processing device (target cost calculation device) 18 Display (display means) 32 Target body shape setting unit (setting means) 34 Body shape estimation unit (estimation means) 38 Cost calculation unit (cost calculation means) 40 Body shape data comparison unit (comparison means) 42 Notification processing unit (notification processing means)

Claims

1. a setting means for setting target body data indicating a target body; a cost calculation means for calculating a cost required for the subject to reach the target body shape based on the measured physical data of the subject and the target physical data; an estimation means for estimating future physical data indicating the subject's body after a predetermined period of time has passed based on the measured physical data of the subject; Equipped with the cost calculated by the cost calculation means corresponds to a level of strain required for the subject to reach the target body, which is determined based on a difference between the physical data of the subject at an arbitrary time point and the target physical data, and a period from the arbitrary time point to a time point when the subject reaches the target body; the cost calculation means calculates a cost required to reach the target physical data from the future physical data estimated by the estimation means; Information processing device.

2. 2. The information processing device according to claim 1, wherein the cost calculated by the cost calculation means corresponds to the degree of burden, which is a value obtained by dividing the difference between the subject's physical data at any given time and the target physical data by the period from the any given time to the time when the subject reaches the target body.

3. the body is the body shape of the subject; The information processing device according to claim 1 , wherein an image showing the subject's body shape after the predetermined period of time has elapsed and a target body shape estimated by the estimation means is displayed on a display means.

4. 4. The information processing device according to claim 1, wherein the cost is at least one of the amount of money, time, and amount of exercise required by the subject to reach the target body, and information indicating the state of the exercise performed to reach the target body.

5. a comparison means for comparing the target physical data with the physical data indicative of the subject's body; 5. The information processing device according to claim 1, further comprising: a notification processing unit that performs notification processing when the physical data reaches the target physical data.

6. a first step in which a setting means sets target body data indicating a target body; a second step in which a cost calculation means calculates a cost required for the subject to reach the target body shape based on the measured physical data of the subject and the target physical data; and the cost calculated by the cost calculation means corresponds to a level of strain required for the subject to reach the target body, which is determined based on a difference between the physical data of the subject at an arbitrary time point and the target physical data, and a period from the arbitrary time point to a time point when the subject reaches the target body; an estimation means for estimating future physical data indicating the body of the subject after a predetermined period of time has elapsed based on the measured physical data of the subject; the cost calculation means calculates a cost required to reach the target physical data from the future physical data estimated by the estimation means; How to create motivation to exercise.

7. Computer, a setting means for setting target body data indicating a target body; a cost calculation means for calculating a cost required for the subject to reach the target body shape based on the measured physical data of the subject and the target physical data; an estimation means for estimating future physical data indicating the subject's body after a predetermined period of time has passed based on the measured physical data of the subject; and make it work, the cost calculated by the cost calculation means corresponds to a level of strain required for the subject to reach the target body, which is determined based on a difference between the physical data of the subject at an arbitrary time point and the target physical data, and a period from the arbitrary time point to a time point when the subject reaches the target body; the cost calculation means calculates a cost required to reach the target physical data from the future physical data estimated by the estimation means; A program to create motivation for exercise.

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