Prediction device, prediction method, and prediction program

Abstract

To provide a prediction device, a prediction method, and a prediction program that aim to improve the quality of life of users.SOLUTION: In a provision system in which an information provision device 10 which is an example of a prediction device, and a terminal device 100 used by a user perform communication between networks, the prediction device has: an acquisition unit 42 that acquires user information which is a content provided to the user and indicates the user's physical characteristics; a prediction unit 44 that predicts a time period where menarche occurs in the user based on the user information; and a provision unit 45 that provides information indicating the possibility that menarche may occur at each time period of menarche indicated by a prediction result by the prediction unit.SELECTED DRAWING: Figure 6

Description

Technical Field

[0001] The present invention relates to a prediction device, a prediction method, and a prediction program.

Background Art

[0002] Conventionally, a technique for improving the quality of life (QOL) of users by providing information related to absorbent articles is known. As an example of such a technique, a technique for delivering physical advice to a user based on the user's menstrual history is known.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Non-Patent Documents

[0004]

Non-Patent Document 1

Non-Patent Document 2

Non-Patent Document 3

Non-Patent Document 4

Non-Patent Document 5

[0005] However, the above-mentioned conventional technologies leave room for improving the quality of life of users.

[0006] For example, conventional technologies only provide physical advice based on the user's menstrual history, and therefore are unable to provide advance advice, such as preparing absorbent articles, before the user experiences menarche.

[0007] The present application has been made in view of the above, and aims to improve the quality of life of users. [Means for solving the problem]

[0008] The prediction device according to the present application is characterized by having an acquisition unit that acquires user information input into content provided to a user for inputting user information indicating the physical characteristics of the user, a prediction unit that predicts the time of menarche of the user based on the user information, and a provision unit that provides information indicating the possibility of menarche occurring at each time of menarche indicated by the prediction result by the prediction unit. [Effects of the Invention]

[0009] According to one aspect of the embodiment, the quality of life of a pre-menarcheal user can be improved. [Brief explanation of the drawings]

[0010]

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DETAILED DESCRIPTION OF THE INVENTION

[0011] At least the following matters become clear from the description of this specification and the accompanying drawings.

[0012] A prediction apparatus comprising: an acquisition unit that acquires user information indicating physical characteristics of a user; and a prediction unit that predicts the timing when the user's menarche occurs based on the user information.

[0013] Such a prediction device predicts the timing of the user's first menstruation based on the user's physical characteristics. As a result of such processing, the prediction device can prompt the user to prepare various absorbent articles before the first menstruation occurs, or notify the user that the first menstruation has occurred, thereby reducing the psychological burden when the first menstruation occurs and improving the user's quality of life.

[0014] In addition, the prediction device acquires information indicating the user's body shape as user information. For example, the prediction device acquires information indicating the user's height and weight. Then, the prediction device predicts the timing of the first menstruation based on changes in height and weight. For example, the prediction device identifies changes in the user's physical characteristics based on the user information, and predicts the timing of the user's first menstruation based on the timing when the identified changes meet a predetermined condition.

[0015] For example, the prediction device identifies the timing when the amount of change in the user's physical characteristics is maximum, and sets the timing when a predetermined period has elapsed from the identified timing as the timing when the user's first menstruation occurs. For example, the prediction device acquires user information indicating the user's height, and sets the timing when a predetermined period has elapsed from the timing when the amount of change in the user's height is maximum as the timing when the user's first menstruation occurs.

[0016] Also, for example, the prediction device acquires user information indicating the user's weight, and sets the time when a predetermined period has elapsed since the time when the change amount of the user's weight is maximum as the time when the user's menarche occurs. Further, the prediction device may acquire information indicating the user's height and weight as user information, and predict the time when the user's menarche occurs based on a predetermined index calculated from the user's height and weight. For example, after the change amount of the user's height becomes maximum and the change amount of the user's weight becomes maximum, the prediction device may set the time when a predetermined period has elapsed since the time when the weight of the user's bones estimated from the user's height and weight satisfies a predetermined condition as the time when the user's menarche occurs. Further, the prediction device may estimate characteristics related to the user's growth based on the height and weight, and set the time when a period corresponding to the characteristics related to the user's growth has elapsed since the time when the change amount of the user's height is maximum as the time when the user's menarche occurs. Further, the prediction device may further acquire information related to the user's psychological changes as user information, and predict the time when the user's menarche occurs based on the information related to the user's psychological changes. Further, among the information related to the user's psychological changes, the prediction device may acquire information related to the user's positive psychological changes, and predict the time when the user's menarche occurs based on the information related to the user's positive psychological changes. Further, among the information related to the user's psychological changes, the prediction device may acquire information related to the user's negative psychological changes, and predict the time when the user's menarche occurs based on the information related to the user's negative psychological changes.

[0017] As a result of each of the above-described processes, the prediction device can appropriately predict the time when the user's menarche occurs. The reason why the time when the user's menarche occurs can be predicted based on the user's body type such as height and weight will become clear in the explanation described later.

[0018] Here, changes in the user's physical characteristics may vary depending on seasons and the like. Therefore, if the user's physical characteristics are identified within a short period and the identified characteristics are used, noise may occur in the amount of change, and there is a risk that the onset age of menstruation cannot be predicted appropriately. Thus, the prediction device acquires user information indicating the user's physical characteristics measured during the same period each year. As a result of such processing, the prediction device can appropriately predict the onset age of menstruation of the user.

[0019] In addition, the prediction device acquires information regarding the user's secretions such as vaginal discharge. As a result of such processing, the prediction device can appropriately predict the onset age of menstruation of the user.

[0020] Further, the prediction device acquires the user information of the target user to be predicted for the onset age of menstruation, and uses a model that has learned the relationship between the user information of the user and the onset age of menstruation of the user to predict the onset age of menstruation of the target user from the user information of the target user. As a result of such processing, the prediction device can appropriately predict the onset age of menstruation of the target user.

[0021] In addition, the prediction device has a providing unit that provides information according to the prediction result. Then, the prediction device provides information regarding the absorbent article according to the prediction result. Further, the prediction device may distribute content corresponding to the user's physical characteristics according to the prediction result. For example, when the prediction result indicates that menstruation has started, the prediction device may provide content for managing menstruation and menstruation. Also, when the prediction result indicates that menstruation has not started, the prediction device may provide content for predicting the onset age of menstruation. As a result, the prediction device can prompt the user for the onset age of menstruation and preparation of absorbent articles, and reduce the psychological burden on the user.

[0022] In addition, the prediction device has an estimation unit that estimates the aspects of the secondary sexual characteristics of the user based on the user information, and provides information regarding the estimated aspects of the secondary sexual characteristics. Further, the prediction device may provide information regarding the absorbent article according to the aspects of the secondary sexual characteristics. For this reason, as a result of the prediction device providing the user with information indicating various changes related to secondary sexual characteristics such as menarche and hair growth, etc., the psychological burden on the user can be reduced.

[0023] In addition, the prediction device predicts the time when the user's menarche occurs based on the aspects of the secondary sexual characteristics estimated by the estimation unit. As a result of such processing, the prediction device can further improve the prediction accuracy of the menarche time.

[0024] In addition, the prediction device has an estimation unit that estimates the cognitive ability of the user based on the user information. And the prediction device predicts the time when the user's menarche occurs based on the estimated cognitive ability. As a result of such processing, the prediction device can further improve the prediction accuracy of the menarche time.

[0025] In addition, the prediction device provides information regarding the absorbent article according to the cognitive ability. For example, the prediction device provides information regarding the method of using the absorbent article according to the cognitive ability. In a more specific example, when the cognitive ability is equal to or higher than a predetermined threshold, the prediction device may provide information regarding the method of using the absorbent article in which the amount of information on the method of using the absorbent article is less than the predetermined threshold. Also, when the cognitive ability is less than the predetermined threshold, the prediction device may provide information regarding the method of using the absorbent article in which the amount of information on the method of using the absorbent article is equal to or higher than the predetermined threshold. In this way, since the prediction device provides information regarding the absorbent article according to the cognitive ability, it can provide the user with appropriate information regarding the absorbent article.

[0026] Hereinafter, an example of an embodiment (hereinafter referred to as the "embodiment") for implementing a prediction device, a prediction method, and a prediction program will be described in detail with reference to the drawings. Note that the prediction device, the prediction method, and the prediction program are not limited by this embodiment. Also, in the following embodiments, the same parts are denoted by the same reference numerals, and redundant explanations are omitted.

[0027] 〔Embodiment〕 〔1. About an example of a providing system〕 First, an example of a providing system according to the embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram showing an example of the providing system according to the embodiment. As shown in FIG. 1, the providing system includes an information providing device 10 which is an example of a prediction device, and a terminal device 100 used by a user U. Note that the providing system may have an arbitrary number of information providing devices 10 and terminal devices 100. Also, the information providing device 10 may execute the processes described later with any number of terminal devices 100.

[0028] The information providing device 10 is an information processing device that performs prediction processing, and is realized by, for example, a server device or a cloud system. For example, the information providing device 10 communicates with the terminal device 100 via a network N (see, for example, FIG. 6), such as various mobile communication systems including LTE (Long Term Evolution), 4G (Generation) including LTE-Advanced, 5G which will be standardized in the future, and various wireless communication networks or various wired communication networks such as Wifi (registered trademark) or wireless LAN (Local Area Network).

[0029] The terminal device 100 is a terminal device used by the user U, which is realized by a smart device such as a PC (Personal Computer), a server device, a smart television, a smartphone, or a tablet, and can communicate with the information providing device 10 via the network N. Further, the terminal device 100 may have a screen such as a liquid crystal display, which has a function of a touch panel, and has a function of receiving various operations on the content distributed from the information providing device 10, such as a tap operation, a slide operation, and a scroll operation, by a finger or a stylus from the user.

[0030] [1-1. About secondary sexual characteristics] Here, when the user U is a female, although there are individual differences, physical changes due to secondary sexual characteristics, such as breast development and the growth of pubic hair, occur approximately during the period from 6 to 17 years old. For such physical changes, various physical development stages are classified by Tanner (see, for example, Non-Patent Document 1).

[0031] Here, when the user U reaches secondary sexual characteristics, according to physical development, vaginal discharge and menstrual blood secretion will occur. When such vaginal discharge and menstrual blood secretion occur, the user will cope with the secretions by using absorbent articles for women.

[0032] The absorbent article for women is various sanitary products related to women's physiology. Specific examples include panty liners for vaginal discharge, napkins and tampons for menstrual blood, but the embodiments are not limited thereto. For example, the absorbent article may be an absorbent article such as a urine leakage pad, a type that can be attached to various underwear, an underwear type, or a sheet type. Further, the absorbent article may be an absorbent article such as a diaper. In the following example, as an example of the absorbent article, an example where the absorbent article is a napkin for absorbing menstrual blood is given, but here, the absorbent article may be a consumable material including the absorbent article.

[0033] Here, until the user U experiences menarche, they have little knowledge about absorbent articles. In particular, when the user U is in puberty, it is considered that they have little awareness of obtaining information about absorbent articles. However, when something is secreted for the first time or when menarche occurs, if the user has not prepared absorbent articles, there is a risk of leakage of secretions. Thus, when leakage of secretions occurs, the secretions adhere to underwear, clothing, bedding such as sheets, etc., and processes such as washing or hand-washing tend to become a stress for the user. Also, when something is secreted for the first time or when menarche occurs, since it is the user U's first experience, the psychological burden tends to increase.

[0034] To reduce such a psychological burden on the user U, it is considered effective to provide advice such as preparation of absorbent articles in advance before the user experiences menarche. Also, by providing such advice, it is considered possible to give motivation to use a service that provides information about absorbent articles before menarche.

[0035] [[1-2. About the outline of prediction processing]] Therefore, the information providing device 10 executes the following prediction processing. First, the information providing device 10 acquires user information indicating the physical characteristics of the user. For example, the information providing device 10 acquires information indicating the body type of the user. Then, based on the acquired information, the information providing device 10 predicts the timing when the user's menarche occurs. More specifically, the information providing device 10 identifies changes in physical characteristics and predicts the timing when the user's menarche occurs based on the timing when the identified changes satisfy a predetermined condition.

[0036] Here, the prediction principle of the timing when menarche occurs (hereinafter, may be described as "menarche timing") will be explained. For example, as such a prediction method for the menarche timing, a correspondence where the average age when menarche occurs is taken as the menarche timing is also conceivable. However, it is known that there are variations in such menarche timing depending on the growth pattern of the user.

[0037] For example, FIG. 2 is a graph showing an example of the physical differences at the onset of menarche. In FIG. 2, with the age on the horizontal axis and the BMI (Body Mass Index) on the vertical axis, graphs showing the BMI at each age for each group with a different age at which menarche occurred are shown (cited from Non-Patent Document 2). As shown in FIG. 2, the BMI of the user group (early-onset group) that reached menarche at a relatively early stage around 11 years old is higher than the BMI of the user group (intermediate group) that reached menarche at an average stage around 12 years old, and the BMI of the user group (late-onset group) that reached menarche at a relatively late stage around 13 years old tends to be lower than the BMI of the intermediate group. Thus, it can be understood that there is a deviation in the timing of reaching menarche depending on the physical characteristics of the user.

[0038] Also, it is known that the timing of menarche of the user changes not only depending on the user's BMI but also depending on the growth pattern of the user (see, for example, Non-Patent Document 3). FIG. 3 is a graph showing an example of the period from the maximum growth age to the age of menarche. In the example shown in FIG. 3, with the relative age on the horizontal axis and the growth rate of height on the vertical axis, growth curves showing the growth rate of height at each average age for each of the early-onset group, intermediate group, and late-onset group are shown (cited from Non-Patent Document 3). In FIG. 3, for the growth curve of each group, the age at which the growth rate is maximum (maximum) is set at the position indicated by a dotted line as the maximum growth age, and the average age of menarche of each group is shown by a line in the same manner as the growth curve.

[0039] As shown in FIG. 3, in the early-onset group where the BMI is higher than the intermediate group, menarche occurs when 0.95 years have elapsed from the maximum growth age, in the intermediate group, menarche occurs at 1.48 years from the maximum growth age, and in the late-onset group where the BMI is lower than the intermediate group, menarche is likely to occur at 1.98 years from the maximum growth age. Thus, it can be understood that menarche is likely to occur when a predetermined period (a period corresponding to the physical characteristics of the user) has elapsed from the maximum growth age at which the growth rate of the user's height is maximum.

[0040] In this way, the user's physical characteristics have a significant relationship with the timing when the user experiences menarche. Therefore, the information providing device 10 predicts the timing of the user's menarche based on the user's physical characteristics. To give a more specific example, the information providing device 10 identifies the timing when the amount of change in the user's physical characteristics is maximized, and sets the timing when a predetermined period has elapsed from the identified timing as the timing when the user's menarche occurs. For example, the information providing device 10 acquires user information indicating the user's height, and sets the timing when a predetermined period has elapsed from the timing when the amount of change in the user's height is maximized (the height spurt period) as the timing when the user's menarche occurs.

[0041] For example, the information providing device 10 acquires information indicating the user's height and weight as user information, and estimates the timing when the user's menarche occurs based on a predetermined index (e.g., BMI, etc.) calculated from the user's height and weight. For example, the information providing device 10 sets the timing when a period corresponding to the characteristics related to the user's growth (e.g., BMI, etc.) has elapsed from the timing when the amount of change in the user's height is maximized as the menarche timing. As a result of such processing, the information providing device 10 can accurately estimate the timing of the user's menarche.

[0042] Note that the information providing device 10 may acquire user information indicating the user's weight, and set the timing when a predetermined period has elapsed from the timing when the amount of change in the user's weight is maximized as the timing when the user's menarche occurs. Also, in FIG. 3, the growth rate of height was used, but it is not limited to this, and only the information on height may be used, and its derivative (i.e., the amount of change) may be used.

[0043] [1-3. An example of prediction processing] Hereinafter, an example of prediction processing will be described with reference to FIG. 1. For example, the terminal device 100 provides diagnostic content as content for predicting the user's menarche (step S1). For example, the terminal device 100 may have an application for providing diagnostic content installed in advance, and may acquire various responses from the user. For example, the information providing device 10 or a predetermined external server (not shown) may cooperate to provide such diagnostic content.

[0044] In the example shown in FIG. 1, the terminal device 100 displays content having a title such as "When will the diagnosis be made" and having a button with text such as "Diagnose" arranged thereon. Then, when the user taps the button, the terminal device 100 provides content for inputting information indicating various physical characteristics of the user (i.e., user information), and obtains various responses such as the user's height and weight (step S2).

[0045] For example, FIG. 4 is a diagram showing an example of content for obtaining user information. As shown in FIG. 4, the terminal device 100 displays content C10 for receiving inputs such as the user's weight, breast development status, bra size, etc. Then, the terminal device 100 receives inputs of each piece of information from the user by means of selection means such as radio buttons. Note that the terminal device 100 may receive responses not only in the form of radio buttons but also in a pull-down format, and may receive various pieces of information from the user via a text box.

[0046] In addition to the information shown in FIG. 4, the terminal device 100 may also receive various pieces of information useful for predicting the user's menarche. For example, the terminal device 100 may receive inputs of information indicating physical characteristics such as the user's age, body type (height and weight), presence or absence of menstruation and discharge, information on various physical changes indicating aspects of secondary sexual characteristics, mother's menarche age, presence or absence of abdominal pain (i.e., menstrual pain), occurrence pattern of armpit hair, occurrence pattern of pubic hair, occurrence pattern of calf hair, etc.

[0047] Further, the terminal device 100 may also receive from the user the amount of sleep, physical discomfort, amount of exercise, etc. For example, the terminal device 100 may receive the average sleep time for a recent predetermined period (e.g., one week). Also, the terminal device 100 may receive information as to whether the user's physical condition for a recent predetermined period is good or poor. Further, the terminal device 100 may receive the average exercise time for a recent predetermined period. Here, the exercise time may include the exercise time for each exercise with different intensities.

[0048] In addition, the terminal device 100 may receive input of information indicating not only the physical characteristics of these users, but also, for example, information indicating the psychological characteristics of the users, such as the presence or absence of a boyfriend or a favorite person, and impressions of a questionnaire. Further, the terminal device 100 may receive, for example, the user's impressions of the absorbent article, and may receive the user's hobbies and preferences (for example, favorite colors, favorite patterns, etc.).

[0049] Also, the terminal device 100 does not need to receive answers for all of the above-described various types of information. For example, when the user only inputs his or her height and weight among the various types of information, the terminal device 100 will predict the user's menarche age using only the height and weight without using other information.

[0050] Returning to FIG. 1 and continuing the explanation. When the terminal device 100 acquires response information from the user, the acquired response information is transmitted to the information providing device 10 (step S3). In such a case, the information providing device 10 identifies the time when the change in physical characteristics is maximized and the growth pattern (step S4). For example, the information providing device 10 identifies the history of the user's height, and calculates the amount of change in height for each predetermined period (for example, one year) from the identified history. Then, the information providing device 10 sets the time when the amount of change in the user's height is maximized as the height spurt time.

[0051] In addition, the information providing device 10 calculates the BMI value using a predetermined formula from the height and weight (step S5). Note that, in addition to the BMI, the information providing device 10 may obtain growth information (hereinafter referred to as "growth information") indicating the growth status of the user from any information. Further, in order to identify the period when the change amount of the height is the largest, the information providing device 10, for example, provides a question to the user such as "When was the time when your height increased the most?" and accepts the input of the user's answer, thereby identifying the period when the change amount of the height is the largest. That is, the process of the information providing device 10 identifying the change in the physical characteristics from the user information indicating the physical characteristics of the user includes not only the process of identifying the change amount from various measurement values such as height and weight and the process of identifying the timing when the change amount is the largest, but also the process of identifying the change amount by obtaining the information indicating the change amount input by the user and the process of identifying the timing when the change amount input by the user is the largest by obtaining the information indicating the timing when the change amount is the largest.

[0052] Then, the information providing device 10 predicts the onset age from the height spurt period and the BMI. For example, the information providing device 10 sets the period elapsed according to the BMI from the height spurt period as the onset age of the user. More specifically, the information providing device 10 calculates the possibility that the onset occurs when a predetermined period such as 3 months later, within 1 year, or within 3 years has elapsed. In actuality, the information providing device 10 predicts the onset age of the user using a model that has been learned using learning data having the height spurt period, the BMI, and the onset age as features. The details of such a model will be described later.

[0053] Subsequently, the information providing device 10 generates the content corresponding to the predicted onset age as proposed content (step S7). Then, the information providing device 10 transmits the generated proposed content to the terminal device 100 (step S8).

[0054] For example, FIG. 5 is a diagram showing an example of proposed content generated by the information providing apparatus according to the embodiment. As shown in FIG. 5, the information providing apparatus 10 generates proposed content C20 that indicates the possibility of the first menstruation occurring at each time period and shows various sanitary products proposed to the user.

[0055] For example, when the possibility of the first menstruation occurring within 3 months is "30 percent", the possibility of the first menstruation occurring within 6 months is "50 percent", the possibility of the first menstruation occurring within 1 year, and the possibility of the first menstruation occurring within 3 years is "10 percent", the information providing apparatus 10 generates proposed content C20 that includes information indicating the period with the highest possibility. For example, the information providing apparatus 10 generates proposed content C20 that emphasizes that the "probability of coming within 6 months" is "50 percent" and shows the possibility of the first menstruation occurring in other periods as a diagnosis result.

[0056] In addition, when the possibility of the first menstruation occurring within 3 months or within 6 months is high, the information providing apparatus 10 generates proposed content C20 that shows various absorbent articles estimated to suit the user, together with a message such as "It's about time to start preparing. What we recommend for you is...". That is, when the first menstruation period satisfies a predetermined condition, the information providing apparatus 10 provides information regarding absorbent articles. For example, the information providing apparatus 10 estimates the user's hip size from the height and weight, and selects various sanitary products such as panty liners #1, napkins #2, shorts #3, etc. of a size that matches the user's physical characteristics from the estimated hip size, and may generate proposed content C20 that shows the selected sanitary products.

[0057] In this way, the information providing apparatus 10 predicts the user's first menstruation period based on the user's physical characteristics and provides proposed content corresponding to the predicted first menstruation period. Therefore, the information providing apparatus 10 can prompt the user U before the first menstruation to prepare absorbent articles and indicate that there will be a future first menstruation, thus reducing the anxiety about dealing with the first menstruation and the stress caused by being unable to cope with the first menstruation, and as a result, improving the quality of life of the user U.

[0058] [[About an example of the functional configuration]] Hereinafter, an example of the functional configuration for realizing the above-described prediction process will be described. In the following description, the outline of the functional configuration of the information providing apparatus 10 will be described, and then an example of the process performed by the functional configuration of the information providing apparatus 10 will be described.

[0059] [[2-1. About the outline of the functional configuration of the information providing apparatus 10]] FIG. 6 is a diagram showing an example of the functional configuration of the information providing apparatus 10 according to the embodiment. As shown in FIG. 6, the information providing apparatus 10 includes a communication unit 20, a storage unit 30, and a control unit 40.

[0060] The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the terminal device 100. For example, the communication unit 20 is realized by a communication circuit or the like.

[0061] The storage unit 30 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk, and various data for executing output processing is registered. For example, in the example shown in FIG. 6, a user database 31 and a model database 32 are registered in the storage unit 30.

[0062] In the user database 31, user information is registered as information regarding each user. For example, FIG. 7 is a diagram showing an example of information registered in the user database according to the embodiment. As shown in FIG. 7, in the user database 31, a user ID (Identifier) and response information are registered in association with each other. More specifically, in the user database 31, information having items such as a response information ID, date and time, height, weight, presence or absence of vaginal discharge, hair growth information, and pain information is registered as response information. In addition to the information shown in FIG. 7, various types of information indicating the physical characteristics of the user may be registered in the user database 31, and various types of information indicating the psychological characteristics of the user may also be registered.

[0063] Here, the "user ID" is an identifier for identifying a user. Also, the "response information ID" is information for identifying response information. As shown in FIG. 7, in the user database 31, a plurality of response information regarding the user indicated by the same user ID and registered at different dates and times will be registered.

[0064] Here, the "date and time" is information indicating the date and time when the response information was registered. Also, the "height" is information indicating the height of the user at the time when the response information was registered, and the "weight" is information indicating the weight of the user at the time when the response information was registered. Also, the "presence or absence of vaginal discharge" is information indicating whether or not there is secretion of vaginal discharge at the time when the response information was registered. Also, the "hair growth information" is information indicating whether or not there is hair growth such as pubic hair or armpit hair at the time when the response information was registered. Also, the "pain information" is information indicating whether or not there is menstrual pain or the like at the time when the response information was registered.

[0065] In the example shown in FIG. 7, the user database 31 stores information such as user ID "UID#1", response information ID "ID#1-1", date and time "2019 / 05 / 01", height "140", weight "46", presence of menstruation "yes", hair growth information "hair growth", and pain information "pain". Such information is registered as one of the response information regarding the user indicated by the user ID "UID#1", and the response information indicated by the response information ID "ID#1-1" is registered, indicating that this response information shows the physical characteristics, etc. of the user at the date and time "2019 / 05 / 01". Also, this response information indicates that the height of the user indicated by the user ID "UID#1" is "140" centimeters, the weight is "46" kilograms, menstruation is secreted, there is hair growth on the armpits and pubic area, and there is menstrual pain.

[0066] Returning to FIG. 6, the description continues. The model database 32 stores data of a model used for predicting the age of menarche of a user. For example, in the model database 32, when information indicating the physical characteristics of the target user for whom the age of menarche is to be predicted is input, a model that has been learned to output information indicating the age of menarche of the target user is registered. Note that various parameters constituting the model are registered in the model database 32, and illustration thereof is omitted.

[0067] The control unit 40 is, for example, an arithmetic processing device for executing various processes, and is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), etc., when various programs (corresponding to an example of a prediction program) stored in a predetermined storage device (for example, the storage unit 30) are executed with the RAM as a work area. Also, the control unit 80 may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0068] In the example shown in FIG. 6, the control unit 40 includes a learning unit 41, an acquisition unit 42, a specifying unit 43, a prediction unit 44, and a providing unit 45. The learning unit 41 executes a learning process described below, and the acquisition unit 42, the specifying unit 43, the prediction unit 44, and the providing unit 45 execute a prediction process described below.

[0069] [2-2. Regarding the learning process] The learning unit 41 learns a model that learns the relationship between user information indicating the physical characteristics of various users and the timing of menarche of the user. Hereinafter, with reference to FIG. 8, an example of the flow of the learning process executed by the learning unit 41 will be described.

[0070] FIG. 8 is a flowchart showing an example of the flow of the learning process executed by the information providing apparatus according to the embodiment. For example, the learning unit 41 acquires information indicating the physical characteristics of a user who has experienced menarche at each time (step S101). Subsequently, the learning unit 41 corrects the parameters of the model so as to output the possibility of menarche occurring when a predetermined period has elapsed when the physical characteristics are input (step S102). That is, the learning unit 41 causes the model to learn the characteristics having a relationship between the physical characteristics and the timing of menarche. Then, the learning unit 41 registers the model in the model database 32 (step S103) and ends the process.

[0071] Hereinafter, an example of such a model will be described. Note that any type of model can be adopted as the model described below. For example, the information providing apparatus 10 may adopt an SVM (Support Vector Machine) or a DNN (Deep Neural Network) as the model. Here, the DNN may be a CNN (Convolutional Neural Network) or an RNN (Recurrent Neural Network). Further, the RNN may be an LSTM (Long short-term memory) or the like. Further, the model may be realized by combining a plurality of models, such as a model combining a CNN and an RNN.

[0072] For example, the learning unit 41 acquires various types of information as response information, such as the age at which menarche occurred, the height and weight of the user, and information indicating the state of various secondary sexual characteristics, as information of users who have experienced menarche. Then, the learning unit 41 performs learning of the model so that when information of the same type as the response information is input to the model, information indicating the age at which menarche occurred is output. Note that for such learning of the model, various arbitrary learning methods, such as backpropagation, can be adopted, for example.

[0073] In addition, the learning unit 41 may specify the user's height spurt period from the history of height and weight, and adopt the height spurt period as one of the inputs. Further, the learning unit 41 may adopt the history of the user's BMI as one of the inputs. In addition, the learning unit 41 may also adopt, as one of the inputs, a numerical value indicating the physical characteristics of the user estimated from the user's height, weight, etc. other than these. Further, the learning unit 41 may estimate the size of the user's pelvis from, for example, the size of the waist circumference and hip size, etc., and use the estimated size of the pelvis as one of the features.

[0074] Further, the learning unit 41 may perform learning of the model so as to output a numerical value indicating the menarche period (for example, a value such as "in 3 months"), or may learn a model indicating the possibility of menarche occurring when a predetermined period has elapsed. For example, the learning unit 41 specifies the height, weight, BMI, and state of secondary sexual characteristics 3 months before, 6 months before, 1 year before, and 3 years before menarche occurs as learning data.

[0075] Then, when the learning data 3 months before menarche occurs is input, the learning unit 41 calculates the highest possibility of menarche occurring in 3 months, and when the learning data 6 months before menarche occurs is input, the learning unit 41 calculates the highest possibility of menarche occurring in 6 months, and when the learning data 1 year before menarche occurs is input, the learning unit 41 calculates the highest possibility of menarche occurring in 1 year, and when the learning data 3 years before menarche occurs is input, the learning unit 41 may perform learning of the model so as to calculate the highest possibility of menarche occurring in 3 years.

[0076] [2-3. Regarding prediction processing] Hereinafter, an example of the flow of prediction processing will be described with reference to FIG. 9. FIG. 9 is a flowchart showing an example of the flow of prediction processing executed by the information providing apparatus 10 according to the embodiment.

[0077] For example, the acquisition unit 42 determines whether it is a predetermined processing timing (step S201). For example, when the acquisition unit 42 receives response information from the terminal device 100, it determines that it is the processing timing. Then, when it is not the predetermined processing timing (step S201: No), the acquisition unit 42 waits until the predetermined processing timing. And when it is the predetermined processing timing (step S201: Yes), the acquisition unit 42 acquires the history of the user's response information corresponding to the response information from the user database 31 (step S202).

[0078] For example, the acquisition unit 42 sets the user corresponding to the response information as the target user for whom the first menstruation timing is to be predicted, and acquires user information indicating the physical characteristics of the target user from the user database 31. For example, the acquisition unit 42 acquires information indicating height and weight as information indicating the body type of the target user. Note that, in addition to these pieces of information, the acquisition unit 42 may also acquire the presence or absence of things, the presence or absence of menstrual pain, and the like.

[0079] Subsequently, the specifying unit 43 specifies the spurt period when the change in the physical characteristics of the target user is the largest from the user information acquired by the acquisition unit 42 (step S203). That is, the specifying unit 43 specifies the change in the physical characteristics of the target user based on the user information. For example, the specifying unit 43 calculates the amount of change in height per year, and specifies the period when the calculated amount of change is the largest as the height spurt period. Note that the specifying unit 43 may specify the period when the amount of change in weight is the largest as the weight spurt period.

[0080] In addition, the specifying unit 43 specifies the BMI of the target user from the height and weight of the user acquired at the same time (step S204). For example, the specifying unit 43 may specify the average value of the BMI at each period, or may specify the BMI at the height spurt period or the weight spurt period.

[0081] Then, the prediction unit 44 predicts the timing of menarche based on the sprint timing and BMI (step S205). That is, the prediction unit 44 predicts the timing when menarche occurs for the user based on the user information of the target user.

[0082] For example, the prediction unit 44 acquires the height sprint timing or the weight sprint timing specified by the specifying unit 43 as the timing when the change in the user's physical characteristics satisfies a predetermined condition. Then, the prediction unit 44 predicts the timing when a predetermined period has elapsed from the height sprint timing or the weight sprint timing as the menarche timing of the user. For example, the prediction unit 44 sets the period when a period corresponding to the value of BMI has elapsed from the height sprint timing or the weight sprint timing as the menarche timing.

[0083] Note that the prediction unit 44 predicts the menarche timing using the model learned by the learning unit 41. For example, when the height sprint timing and the value of BMI are input, the learning unit 41 performs learning of the model so as to output the possibility of menarche occurring when each period has elapsed. In such a case, the prediction unit 44 inputs the height sprint timing and the value of BMI of the target user into the model to predict the menarche timing.

[0084] Note that the prediction unit 44 may predict the menarche timing based on a rule, or may predict the menarche timing using various equations. For example, the prediction unit 44 sets the date and time when a period calculated according to the user's BMI has elapsed from the height sprint timing of the user as the menarche timing, and may calculate the period from the prediction time to the menarche timing of the user from the difference between the current age of the user and the menarche timing.

[0085] Subsequently, the providing unit 45 generates providing information according to the prediction result by the predicting unit 44 (step S206). For example, the providing unit 45 generates providing information indicating the possibility of the occurrence of menarche within each period. Further, when the period until the most likely menarche time is shorter than a predetermined threshold, the providing unit 45 may generate providing information indicating information about the absorbent article. Then, the providing unit 45 provides the generated providing information to the terminal device 100 of the target user (step S207) and ends the process.

[0086] 〔3. Regarding variations of the process〕 Hereinafter, variations of the above-described process will be described. Note that the processes described below may be implemented individually or in any combination.

[0087] 〔3-1. Regarding the aspects of secondary sexual characteristics〕 Here, the menarche time of the user is considered to have a close relationship with the aspects of the user's secondary sexual characteristics. For example, things that occur as precursors of menarche are considered to have a high relationship with the aspects of the user's secondary sexual characteristics. Also, menarche is considered to occur after such things are secreted. Therefore, the information providing device 10 may predict the time when the user's menarche occurs based on the aspects of the user's secondary sexual characteristics.

[0088] For example, FIG. 10 is a diagram showing an example of the time when each state group occurs. In the example shown in FIG. 10, regarding breast development and pubic hair growth, the increase and decrease in the number of users classified into each group in the Tanner classification described above are shown for each age.

[0089] For example, in such a Tanner classification (hereinafter referred to as "Tanner classification"), the stages of breast development are classified into the first stage (B1) where only the nipple protrudes, the second stage (B2) where only the nipple protrudes, a small elevation of the breast is formed, and the coloring increases, the third stage (B3) where the areola and breast parenchyma protrude further, but there is no step between the areola part and other parts, the fourth stage (B4) where the areola part protrudes in a disc shape above the mammary parenchyma, and the fifth stage (B5) where a rounded hemispherical breast is formed. Also, in the Tanner classification, the stages of pubic hair growth are classified into the first stage (PH1) where there is no hair growth, the second stage (PH2) where long, slightly colored downy hair, straight or slightly curly, grows sparsely along the labia, the third stage (PH3) where darker and coarser hair grows sparsely above the vagina, the fourth stage (PH4) where it approaches adult-type hair growth but the hair growth area is small, and the fifth stage (PH5) where there is adult-type hair growth.

[0090] As shown in FIG. 10, the number of users classified into the B2 group increases when the user's age is around 7, the number of users classified into the B3 group increases when the user's age is around 8, and the number of users classified into the PH2 group increases when the user's age is around 9. Also, as shown in FIG. 10, the number of users classified into the B4 group or PH3 group increases when the user's age is around 10, the number of users classified into the B5 group or PH4 group increases when the user's age is around 12, and the number of users classified into the PH5 group increases when the user's age is around 14.

[0091] Thus, although the physical changes related to the secondary sexual characteristics of the user vary among users, they are considered to occur with a certain degree of orderliness. Here, considering that the occurrence of menarche has a close relationship with the aspects of secondary sexual characteristics and that menarche occurs after the occurrence of menarche, it can be said that the aspects of the user's secondary sexual characteristics are significant information for predicting the user's menarche time.

[0092] Therefore, the information providing apparatus 10 predicts the menarche time of the user based on the mode of the user's secondary sexual characteristics. For example, the information providing apparatus 10 may acquire information indicating the user's state regarding breast development and pubic hair growth, classify the user into each group in Tanner classification based on the acquired information, and predict the user's menarche time based on the classification result. Also, the information providing apparatus 10 may acquire the presence or absence of menses as one of the modes of secondary sexual characteristics and estimate the user's menarche time based on the presence or absence of menses.

[0093] Note that the information providing apparatus 10 may perform classification in any mode as long as it performs classification according to the mode of secondary sexual characteristics other than Tanner classification. Also, the information providing apparatus 10 may use the information indicating the mode of secondary sexual characteristics (that is, the presence or absence of menses and the presence or absence of dysmenorrhea) itself as the estimation result.

[0094] 〔3-2. Features to be Used (1) Mode of Secondary Sexual Characteristics〕 In the above description, the information providing apparatus 10 uses the user's height spurt time and BMI as information (that is, features) for predicting the menarche time. However, the embodiment is not limited to this. For example, the information providing apparatus 10 may predict the menarche time using the mode of secondary sexual characteristics as one of the features. For example, the information providing apparatus 10 may learn the relationship between the mode of secondary sexual characteristics and the menarche time in a model and further use the mode of secondary sexual characteristics of the target user to predict the menarche time. More specifically, the information providing apparatus 10 may input the height spurt time, weight spurt time, presence or absence of menses, Tanner classification result, etc. of the target user and predict the menarche time.

[0095] In addition, if the information providing device 10 estimates the menarche time based on information indicating the physical characteristics of the user including the aspects of secondary sexual characteristics in addition to the above-described information, it may adopt any information and any combination of information. For example, the information providing device 10 may predict the menarche time only from the history of the user's height. For example, the information providing device 10 may set the time when a predetermined date and time has elapsed since the height spurt period as the menarche time. Also, the information providing device 10 may predict the menarche time only from the history of the weight. For example, the information providing device 10 may set the time when a predetermined date and time has elapsed since the weight spurt period when the increase amount of the weight is maximum as the menarche time.

[0096] In addition, the information providing device 10 may predict the menarche time based only on the history of the aspects of secondary sexual characteristics. For example, the information providing device 10 may learn the relationship between the change in the Tanner classification of the user at each age and the menarche time as a model, and predict the menarche time from the change in the Tanner classification of the target user.

[0097] Also, the information providing device 10 may predict the menarche time using a model with any information among the above-described various user information as features. For example, the information providing device 10 may realize a prediction reflecting the genetic relationship by using the mother's menarche time as a feature. Also, the information providing device 10 may perform learning of the model and the like so as to estimate the possibility that the date and time when a predetermined period has elapsed after the occurrence of the first menstruation is the menarche time to be higher.

[0098] Furthermore, the information providing device 10 may estimate the menarche time using other physical information estimated from the above-described various user information. For example, in a general growth pattern, the height spurt and the weight spurt occur either simultaneously or with a time shift, and then there is a high possibility that menarche occurs after the bones become thicker. Therefore, the information providing device 10 estimates the weight of the user's bones from the user information, and after various spurts occur, predicts the time when a predetermined period has elapsed since the time when the weight of the bones satisfies a predetermined condition as the menarche time.

[0099] Furthermore, the information providing device 10 may determine the time of menarche as a period of time that corresponds to the user's growth characteristics (hereinafter referred to as a "prediction grace period") after the time when various growth spurt periods or bone weights satisfy predetermined conditions (hereinafter referred to as a "reference period"). For example, as described above, the information providing device 10 may determine the time of menarche as a period of time that corresponds to the BMI value, or may determine the time of menarche as a predetermined period calculated from height and weight, for example. Furthermore, the information providing device 10 may determine the time of menarche as a period of time that corresponds to the state of secondary sexual characteristics.

[0100] The information providing device 10 may learn the relationship between such various reference periods and the predicted grace period into a model, and may predict the period until menarche (i.e., the predicted grace period of the target user) by inputting the reference period of the target user. By performing such processing, the information providing device 10 can more accurately estimate the time of menarche of the user.

[0101] The information providing device 10 may use information according to fluctuations in height or weight as a feature in addition to the height spurt periods. For example, the information providing device 10 may use, as a feature, the timing when height starts to grow (for example, the timing when the slope of a graph showing height growth starts to become positive) in addition to the height spurt periods. Similarly, the information providing device 10 may use, as a feature, the timing when weight, bone weight, etc. start to increase.

[0102] In addition, in a typical growth pattern, a baby's growth rate goes through a first growth spurt after birth, slows down temporarily, and then experiences a second growth spurt. In the above explanation, the information providing device 10 predicts the time of menarche based on the second growth spurt. However, for example, the information providing device 10 may inquire of the user's parents or other relatives about the time of the first growth spurt and use the inputted time as a further feature. In other words, the information providing device 10 may use any information as a feature, as long as the information indicates the user's physical characteristic history.

[0103] [3-3. Features to be utilized (2) Psychological changes] Also, in the above description, the information providing apparatus 10 used the user's height spurt period and BMI as information for predicting the onset of menstruation. However, the embodiment is not limited thereto. For example, the information providing apparatus 10 may predict the onset of menstruation using the user's psychological changes as information for predicting the onset of menstruation.

[0104] For example, the information providing apparatus 10 acquires, as response information, information regarding the user's psychological state and psychological changes with respect to physiology. For example, the information providing apparatus 10 acquires information regarding whether the user is positive or negative about physiology from questions regarding physiology. For example, when responses such as "I can become an adult", "Not yet", or "Can't it come soon" are obtained for questions regarding physiology, the information providing apparatus 10 determines that the user is positive about physiology. On the other hand, when responses such as "It's troublesome" or "It hurts" are obtained for questions regarding physiology, the information providing apparatus 10 determines that the user is negative about physiology. Also, when responses indicating a negative mood such as "What's it like", "What should I do when it happens", or "I don't want to become it" are obtained for questions regarding physiology, the information providing apparatus 10 determines that the user is negative about physiology. In this way, the information providing apparatus 10 acquires the user's current straightforward feelings about the coming of physiology.

[0105] Note that the input mode for questions regarding physiology may be any mode. For example, the input mode may be a radio button format for selecting the content closest to the user's mood, a checkbox format for selecting multiple contents suitable for the user's psychological state, a format for allowing the user to input an answer in free form, or the like.

[0106] Here, when the information providing device 10 is input in free form by the user, the input information input in free form by the user is analyzed using conventional techniques related to natural language processing such as morphological analysis and semantic analysis. For example, the information providing device 10 refers to a predetermined database in which words indicating a mental state and mental changes are stored in advance in association with the positive or negative meaning indicated by such words, and calculates the frequency of occurrence of the words included in the input information. Then, based on the calculation result, when the frequency of occurrence of positive words among the words indicating the mental state and mental changes is equal to or greater than a predetermined threshold, the information providing device 10 determines that the user is positive about physiology. On the other hand, based on the calculation result, when the frequency of occurrence of negative words among the words indicating the mental state and mental changes is equal to or greater than a predetermined threshold, the information providing device 10 determines that the user is negative about physiology. Note that the predetermined database may be possessed by the information providing device 10, or may be possessed by an external server or an external cloud system.

[0107] In addition, the information providing device 10 may acquire information regarding the user's mental state and mental changes with respect to physiology by using a method of having the user select an illustration or an image like a questionnaire or by using a psychological test such as POMS (Profile of Mood States).

[0108] In addition, the information providing device 10 may estimate information regarding the user's mental state and mental changes with respect to physiology from the information detected by various sensors. For example, when the terminal device 100 or the wearable device used by the user has various sensors, the information providing device 10 may estimate the mental state from the user's heart sound. For example, the information providing device 10 determines whether the user is excited or calm from the user's heart rate when browsing questions regarding physiology.

[0109] For example, the information providing apparatus 10 may vary the frequency of providing the user with questions regarding physiology according to the result of the first menstruation prediction. In this case, the information providing apparatus 10 uses the first question regarding physiology to determine whether the user is positive or negative about physiology for a user predicted to have the first menstruation soon. On the other hand, the information providing apparatus 10 may provide the user predicted to have the first menstruation after a predetermined period (for example, after several months, after several years, etc.) with questions regarding physiology a plurality of times. Then, the information providing apparatus 10 determines whether the user is positive or negative about physiology for each of the questions regarding physiology provided a plurality of times. Further, when the user shows a negative psychological change, the information providing apparatus 10 may periodically provide the user with information regarding physiology that relieves the anxiety about physiology.

[0110] In this way, the information providing apparatus 10 can track the psychological changes of the user regarding physiology over time. Thereby, the information providing apparatus 10 can enable the user to grasp his or her own psychological changes regarding physiology. Further, the information providing apparatus 10 can eliminate the cognitive bias regarding physiology for the user by providing knowledge regarding physiology before the first menstruation. Further, by acquiring the psychological changes of the user, the information providing apparatus 10 can provide information (for example, information regarding whether the menstrual pain is abnormal or normal) that enables control of the user's menstrual pain, premenstrual syndrome (PMS), or premenstrual dysphoric disorder (PMDD). Therefore, the information providing apparatus 10 can encourage control of the user's anxiety.

[0111] Further, the information providing apparatus 10 may provide the user with information regarding sanitary products according to the psychological changes. For example, when the user shows a positive psychological change, the information providing apparatus 10 may provide content regarding sanitary products including the method of using the sanitary products.

[0112] [3-4. Features to be Used (3) Cognitive Ability] Also, in the above description, the information providing apparatus 10 used the user's height spurt period and BMI as information for predicting the onset of menstruation. However, the embodiment is not limited to this. For example, the information providing apparatus 10 may estimate the cognitive ability of the user based on the user information. Then, the information providing apparatus 10 may predict the onset of menstruation using the estimated cognitive ability as information for predicting the onset of menstruation.

[0113] For example, the information providing apparatus 10 may estimate the cognitive ability indicating the development state of the user's brain based on the user information input by the user. Then, the information providing apparatus 10 may predict the onset of menstruation using the estimated cognitive ability. For example, the information providing apparatus 10 may learn the relationship between the estimated cognitive ability and the onset of menstruation in a model, and predict the onset of menstruation using the cognitive ability of the target user. In this way, the information providing apparatus 10 can estimate the development status of the user's cognitive ability and understanding degree according to the change of the cognitive ability due to the breakdown of the psychological balance during puberty. Thereby, the information providing apparatus 10 can accurately predict the onset of menstruation of the user.

[0114] Also, the information providing apparatus 10 may provide information regarding sanitary products including a method of proposing sanitary products and a method of using sanitary products to the user according to the estimated estimation result. For example, when the estimated cognitive ability of the user is less than a predetermined threshold, the information providing apparatus 10 may provide the content CU1 in which the method of using sanitary products is described in detail. Here, the content CU1 may include a detailed description of the sanitary product itself. Also, when the estimated cognitive ability of the user is less than a predetermined threshold, the information providing apparatus 10 may provide the content CU2 for proposing sanitary products with high operability. For example, the content CU2 is content for proposing a product that is easy to wear and highly resistant to leakage as a sanitary product.

[0115] On the one hand, when the estimated cognitive ability of the user is equal to or higher than a predetermined threshold, the information providing device 10 may provide content CU3 in which the usage method of the sanitary product is simply explained and the amount of information of the sanitary product itself is lower than that of content CU1. Further, when the estimated cognitive ability of the user is equal to or higher than a predetermined threshold, the information providing device 10 may provide content CU3 that proposes a sanitary product used by adult women. For example, content CU3 is content that proposes a compact product with low resistance to leakage.

[0116] Thereby, the information providing device 10 can provide information regarding the sanitary product according to the cognitive ability of the user. For example, when the cognitive ability is equal to or higher than a predetermined threshold, it may be troublesome to be explained in detail about the usage method of the sanitary product. For this reason, when the cognitive ability is equal to or higher than a predetermined threshold, the information providing device 10 provides content including a simple explanation with a reduced amount of information on the usage method of the sanitary product. In this way, since the information providing device 10 can propose a sanitary product suitable for the user, the satisfaction of the user can be improved. Therefore, the information providing device 10 can provide the user with information regarding an appropriate sanitary product according to the cognitive development stage and the physical development stage.

[0117] [3-5. Regarding Prediction Processing] Also, in the above description, the information providing device 10 uses the user's height spurt period and BMI as information for predicting the onset age. However, the embodiment is not limited to this. For example, the information providing device 10 may predict the onset age using the height at each predetermined age and the age among the user's height as information for predicting the onset age. For example, when the age of the user is 7 years old, the information providing device 10 may predict the onset age using the height at the age of 7, which is the current age, and the age of 7 years old.

[0118] Hereinafter, while giving an example of the transition of the content displayed on the terminal device 100 using FIG. 11, a prediction process for predicting the first menstruation period using the height and age of the user will be described. FIG. 11 is a diagram showing an example of the transition of the content according to the modified example. In the example of FIG. 11, similar to FIG. 1, it will be described that the terminal device 100 has an application for providing diagnostic content pre-installed.

[0119] For example, in the example of FIG. 11, the terminal device 100 displays content C30 titled "User Settings" in order to register user information. Here, the content C30 includes "Name", a text box IN301 for receiving the name input by the user, "Nickname", a text box IN302 for receiving the nickname input by the user, and a button B301 for proceeding to the next content. In this case, the terminal device 100 receives the input of the name and the input of the nickname from the user, and when the button B301 is pressed by the user, it causes a transition to the content C31.

[0120] Then, the terminal device 100 displays content C31 titled "User Settings" to register information related to the user's physiology among the user information. Here, the content C31 includes "Menstrual period", a text box IN311 for receiving the menstrual period input by the user, "Menstrual cycle", and a text box IN312 for receiving the menstrual cycle input by the user. Furthermore, the content C31 includes radio buttons IN313 with selection items such as "Has not had a first menstrual period yet", "Less than 3 years since the first menstrual period", and "3 years or more since the first menstrual period" to allow the user to select the number of years of menstrual experience, and a button B311 to proceed to the next content. In this case, the terminal device 100 receives the input of the menstrual period, the input of the menstrual cycle, and the selection of the radio button IN313 from the user, and when the button B311 is pressed by the user, it transitions to the content C32. Note that the terminal device 100 may further receive user information other than the question items included in the contents C30 and C31. For example, the terminal device 100 may transition to content that allows the input or selection of other user information other than the above from the content C32.

[0121] Then, the terminal device 100 displays content C32 that explains how to use the content for managing the physiological state. Here, the content C32 includes a pie chart GR321, an explanatory text EX321, a comment CO321, and an explanatory text EX322. For example, the explanatory text EX321 describes content such as "Tap here to record your menstruation!". Also, the explanatory text EX322 describes content such as "Advice according to your menstrual cycle!" and "You can read the continuation by tapping!". Also, the comment CO321 describes content such as "The day when the menstrual flow is the most during menstruation. Change the sanitary napkin when you notice...".

[0122] The terminal device 100 displays various contents according to the input information of the user. For example, the terminal device 100 distributes the contents according to the user's state such as whether the first menstruation has started or not. For example, if the first menstruation has started, the terminal device 100 distributes the contents in the menstrual cycle management mode, and if the first menstruation has not started, the terminal device 100 distributes the contents in the first menstruation prediction mode. Here, the contents corresponding to each mode include different articles and advertisement contents for each mode.

[0123] For example, when the terminal device 100 receives an input from the user indicating that the user's menstruation has started, the terminal device 100 displays the content C33 in the menstrual cycle management mode. Here, the content C33 includes "Next menstrual schedule X / XX", "XX days until the next menstruation", a pie chart GR331 centered on today's date, and a comment CO331. For example, the terminal device 100 displays the content C33 including "Next menstrual schedule 2 / 7", "13 days until the next menstruation", and as the comment CO331, "The secretion amount of hormones that create femininity increases, and it is a time when motivation and concentration improve...". In this way, the terminal device 100 can easily let the user grasp the user's own menstrual state. In addition, since the terminal device 100 provides comments and advice according to the user's menstrual state, the user can easily notice the changes in the user's own physical condition.

[0124] A calendar may be attached to the lower part of the content C33. For example, information regarding the user's hormone balance, physical condition, etc., which is stored in association with the date indicated by such a calendar, may be displayed on the content C33 according to the user's operation.

[0125] On the other hand, when the terminal device 100 does not receive an input from the user when the user's menstruation has started, it displays the content C34 in the first menstruation prediction mode. Here, the content C34 includes a pie chart GR341 with "Predicted date last time: 20XX / X / XX" and "Probability of coming within half a year: 50%" displayed at the center, and a comment CO341. For example, the terminal device 100 displays the content C34 including "Predicted date last time: 2020 / 2 / 10" and, as the comment CO341, "Advice will be displayed and you can read the continuation if you register your menstrual date! Please register your most recent menstrual date...".

[0126] In this way, the terminal device 100 can easily let the user recognize the predicted date of the first menstruation. Also, the terminal device 100 can provide the user with correct knowledge about menstruation via the comment CO341 at an appropriate timing (for example, before the first menstruation) so that the user can take proper measures for menstruation. For example, the terminal device 100 can provide correct knowledge about menstruation to a user who is likely to have their first menstruation within one year. For example, regarding menstrual pain, it is known that menstrual pain is alleviated when the user has a good menstrual experience. Therefore, the terminal device 100 can improve the quality of the user's life by making the user recognize knowledge about menstrual pain in advance at an appropriate timing.

[0127] Also, generally, the first menstruation period is a time when stress begins to increase due to changes in the life stage, changes in human relationships (for example, the emergence of desire for the opposite sex from an interest in the opposite sex, the rebellious period), etc. In this case, the user may have an unstable mental state that is contrary to the physical growth when they reach the first menstruation. Therefore, the terminal device 100 can provide information at an appropriate timing according to the cognitive development stage and the physical development stage, rather than giving the user a lot of information to choose from.

[0128] In the example of FIG. 11, an example in which the terminal device 100 receives user information input by the user is shown, but it is not necessarily limited to this. For example, when the application is used by a parent and child, the terminal device 100 may receive the user information of the user input by the parent of the user. Thereby, in order for the parent to easily manage the user's physiology, the terminal device 100 can prompt a reminder such as not forgetting the sanitary products from the parent to the user. Also, when the application is used by a parent and child, accounts corresponding to the parent and the user may be generated respectively.

[0129] Also, as an example of the content displayed on the terminal device 100 using FIG. 12, an example of a web page is given. FIG. 12 is a diagram showing an example of a web page according to a modified example. In the example of FIG. 12, it will be described that the terminal device 100 displays a web page for providing diagnostic content using a predetermined browser.

[0130] For example, in the example of FIG. 12, the terminal device 100 displays content C40 titled "First Menstruation Prediction" in order to acquire user information. Here, the content C40 includes "When will it come? You can get an idea of when your menstruation will come! Don't worry just because it hasn't come yet!", "Height", a text box IN41 for receiving the height input by the user, "Date of birth", a text box IN42 for receiving the date of birth input by the user, and a button B41 for transmitting the input information. In this case, the terminal device 100 receives the input of the height and the date of birth from the user, and when the button B41 is pressed by the user, transmits the user information input by the user to the information providing device 10. Then, the information providing device 10 provides the terminal device 100 with content including the first menstruation prediction result predicted based on the transmitted user information.

[0131] In addition, the content C40 further includes advertising content. For example, the content C40 includes advertising content IT41 with content such as "If it's an app, it will follow you until your period comes!!" displayed, and advertising content IT42 with content such as "First period kit on sale!" displayed. For example, the advertising content may be advertising content related to applications, advertising content related to set products of menstrual supplies such as first period kits, or advertising content related to content introducing recommended products based on the first period prediction results. Here, when the advertising content related to the content introducing the recommended products is pressed by the user, the terminal device 100 causes a transition to the content introducing the recommended products. Note that the advertising content mentioned here may be any type of advertising content, for example, a banner advertisement or the like.

[0132] Note that the modification example is not limited to the above example. For example, the terminal device 100 may perform the above processing using a known SNS (Social Networking Service) service. Also, the information providing device 10 may select the advertising content to be displayed in the content C40 based on the information regarding the referrer acquired as user information. Further, the information providing device 10 may select the advertising content to be displayed in the content C40 based on the user information. Additionally, the information providing device 10 may select the advertising content to be displayed in the content C40, which is the advertising content specified by the user.

[0133] [3-6. Regarding the information to be provided] Here, the information providing device 10 may provide the prediction result and the like not only to the target user for whom the first period timing is to be predicted, but also to users who have a predetermined relationship with the target user, such as the parents or teachers of the target user. For example, the information providing device 10 may acquire user information indicating the physical characteristics of the user U from the parent of the user U, and provide the first period timing of the user U estimated from the acquired user information to the parent of the user U. Also, the information providing device 10 may provide different content depending on whether the information recipient is the parent or the child.

[0134] By performing such processing, the information providing apparatus 10 can promote communication between parents and children. Further, when the information providing apparatus 10 provides the prediction result to the parent, by providing various product information and the latest information regarding physiology or secondary sexual characteristics, it can promote the update of the knowledge of the parent generation and reduce the gap that occurs in the awareness with the target user. Further, the information providing apparatus 10 can cause the parent to prepare absorbent articles for children.

[0135] Further, when the information providing destination is the user U himself / herself, the information providing apparatus 10 may provide information regarding the aspect of secondary sexual characteristics. For example, the information providing apparatus 10 can further reduce the anxiety of the user associated with secondary sexual characteristics by providing content that explains the meaning and explanation of physical changes such as the breasts becoming larger or the growth of pubic hair.

[0136] Note that the information providing apparatus 10 may estimate the future aspect of secondary sexual characteristics from the aspect of secondary sexual characteristics and provide the user with information regarding the estimation result. For example, when it is estimated from the aspect of the user's secondary sexual characteristics that pubic hair will grow in a predetermined period (for example, six months later), the information providing apparatus 10 may provide a message such as "Hair will grow in the delicate area from now on" to reduce the psychological burden of the user associated with secondary sexual characteristics.

[0137] Note that the information providing apparatus 10 may predict not only the time of the first menstruation but also the time when vaginal discharge is secreted for the first time. For example, the information providing apparatus 10 predicts the time when vaginal discharge is secreted for the first time using a model that has learned the relationship between the time when vaginal discharge is secreted for the first time and the user information. Then, when it is predicted that vaginal discharge will be secreted other than in March, the information providing apparatus 10 may provide the user with a message such as "Vaginal discharge may occur, so why don't you try using a panty liner?"

[0138] 〔3-7. Regarding the acquisition timing of user information〕 Here, it is known that physical changes in users, such as height and weight, vary depending on the season. For example, during summer, it is easier to consume energy during the day, resulting in deeper sleep, and as a result, the amount of change in height and weight tends to increase. During winter, it is more difficult to consume energy during the day, resulting in shallower sleep, and as a result, the amount of change in height and weight tends to decrease. Therefore, for example, the amount of change in height and weight measured every month may include different fluctuations for each season, which can become noise for prediction.

[0139] Therefore, the information providing device 10 may predict the onset age based on the amount of change in height and weight measured at intervals longer than a predetermined period. For example, the information providing device 10 may predict the onset age from the height and weight measured at a fixed date and time every year (for example, April 20th every year). By using such information, the information providing device 10 can predict the onset age with higher accuracy.

[0140] In addition, in order to identify the timing when the height begins to increase (the timing when the slope becomes positive in the growth rate graph), by recording height information from a lower age (or, for example, the information providing device 10 provides a question such as "When did the height start to increase?" and accepts input of answers from the user), it is possible to improve the accuracy of predicting the onset of menstruation or provide the onset age from a lower age. Furthermore, it can also be used for predicting the development of breasts, which is a characteristic of secondary growth, the timing of excretion, and future height.

[0141] [Regarding the selection of absorbent articles 3-8.] In the above description, the information providing device 10 selects absorbent articles to propose to users before the onset of menstruation based on various user information. Here, in addition to the various combinations described above, the information providing device 10 may select absorbent articles appropriate for the user (that is, absorbent articles that are less likely to shift, sag, or leak) by any combination.

[0142] In addition, for users whose period until the onset of menarche is below a predetermined threshold, the information providing device 10 may provide a kit that includes various articles for dealing with menarche and books containing explanations about menstruation and secondary sexual characteristics. For example, when the predicted remaining period of the target user is below a predetermined threshold, the information providing device 10 selects the target user as a recipient of a kit that includes underwear such as napkins and shorts in a size suitable for the body type of the target user estimated from the user information, a pouch for storing sanitary products such as napkins, a book on sex education regarding menstruation, and a photo with a message from the mother. Then, the information providing device 10 may execute various processes for shipping the kit to the target user.

[0143] 〔3-9. Others〕 Note that, among the above-described processes, all or part of the processes described as being automatically performed may be manually performed. Also, all or part of the processes described as being manually performed may be automatically performed by a known method. Additionally, regarding the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings, they can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

[0144] Moreover, each component of each illustrated device is conceptually functional and does not necessarily have to be physically configured as shown. That is, the specific form of the dispersion and integration of each device is not limited to that shown. Also, each component may be functionally or physically dispersed and integrated in any unit in accordance with various loads and usage situations, etc., either in whole or in part. Additionally, the above-described processes may be executed in appropriate combination within a non-conflicting range. Also, the "section, module, unit" described above can be read as "means" or "circuit", etc. For example, the prediction unit can be read as a prediction means or a prediction circuit.

[0145] 〔4. Hardware Configuration〕 Further, the information providing apparatus 10 according to the above-described embodiment is realized by, for example, a computer 1000 configured as shown in FIG. 13. FIG. 13 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and an arithmetic unit 1030, a cache 1040, a memory 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected by a bus 1090.

[0146] The arithmetic unit 1030 operates based on programs stored in the cache 1040 or the memory 1050 and programs read from the input device 1020, etc., and executes various processes. The cache 1040 is a cache that primarily stores data used by the arithmetic unit 1030 for various operations, such as a RAM. Further, the memory 1050 is a storage device in which data used by the arithmetic unit 1030 for various operations and various databases are registered, and is a memory realized by a ROM (Read Only Memory), an HDD (Hard Disk Drive), a flash memory, etc.

[0147] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and may be realized by a connector of a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), HDMI (registered trademark) (High Definition Multimedia Interface). On the other hand, the input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, a keyboard, and a scanner, and is realized by, for example, USB or the like.

[0148] For example, the input device 1020 may be realized by a device that reads information from an optical recording medium such as a CD (Compact Disc), DVD (Digital Versatile Disc), or PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Further, the input device 1020 may be realized by an external storage medium such as a USB memory.

[0149] The network IF 1080 has a function of receiving data from other devices via the network N and sending it to the arithmetic unit 1030, and also sending data generated by the arithmetic unit 1030 via the network N to other devices.

[0150] Here, the arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the memory 1050 onto the cache 1040 and executes the loaded program. For example, when the computer 1000 functions as the information providing device 10, the arithmetic unit 1030 of the computer 1000 realizes the function of the control unit 140 by executing the program loaded onto the cache 1040.

[0151] As a method of providing this embodiment, a dedicated application may be installed on the terminal device 100, and the program installed on the information providing device 10 and the application installed on the terminal device 100 may cooperate to provide this embodiment to the user. For example, the application of the terminal device 100 causes the terminal device 100 to execute display processing of an input screen for inputting information indicating the physical characteristics of the user, reception processing for receiving the input, and transmission processing for transmitting the received information to the information providing device 10 as user information. On the other hand, the program of the information providing device 10 causes the information providing device 10 to execute acquisition processing for acquiring user information from the terminal device 100 and prediction processing for predicting the user's menarche time from the user information.

[0152] Further, the terminal device 100 may be equipped with a general-purpose browser and be connected to the information providing device 10 via the general-purpose browser of the terminal device 100 to provide the present embodiment to the user. For example, the information providing device 10 may distribute a web page for receiving input of user information to the terminal device 100 and acquire the user information via the web page to realize the above-described processing.

[0153] [5. Effects] As described above, the information providing device 10 predicts the user's menarche period in advance from the user's physical characteristics. As a result of such processing, the information providing device 10 can prompt the user that menarche will occur in the future and to prepare various absorbent articles, etc., thereby reducing the user's psychological burden and improving the user's quality of life.

[0154] In addition, the information providing device 10 predicts the menarche period from the user's physical change amount and BMI based on the relationship between the physical change amount, physical characteristics such as BMI, and the menarche period, so that the information providing device 10 can accurately estimate the menarche period of the user. As a result, the information providing device 10 can provide information for explaining the response to menarche, secondary sexual characteristics, menstruation, etc. to the user in a more appropriate manner, thereby improving the user's quality of life.

[0155] The embodiments of the present application have been described in detail based on the drawings. However, these are examples, and the embodiments of the present application can be implemented in other forms with various modifications and improvements based on the knowledge of those skilled in the art, starting from the aspects described in the column of the disclosure of the invention.

[0156] [6. Supplementary Note] Note that the present technology can also adopt the following configuration. (1) An acquisition unit that acquires user information indicating the user's physical characteristics, A prediction unit that predicts the time when the user's menarche occurs based on the user information A prediction device characterized by having (2) The acquisition unit acquires information indicating the body type of the user as the user information The prediction device according to (1) above, characterized by this (3) Based on the user information, the prediction unit identifies changes in the physical characteristics of the user, and predicts the timing of the user's first menstruation based on the timing when the identified changes satisfy a predetermined condition The prediction device according to (1) or (2) above, characterized by this (4) The prediction unit identifies the timing when the amount of change in the physical characteristics of the user is maximum, and sets the timing when a predetermined period has elapsed from the identified timing as the timing when the user's first menstruation occurs The prediction device according to (3) above, characterized by this (5) The acquisition unit acquires user information indicating the height of the user, The prediction unit sets the timing when a predetermined period has elapsed from the timing when the amount of change in the height of the user is maximum as the timing when the user's first menstruation occurs The prediction device according to (4) above, characterized by this (6) The acquisition unit acquires user information indicating the weight of the user, The prediction unit sets the timing when a predetermined period has elapsed from the timing when the amount of change in the weight of the user is maximum as the timing when the user's first menstruation occurs The prediction device according to (4) or (5) above, characterized by this (7) The acquisition unit acquires information indicating the height and weight of the user as the user information, The prediction unit predicts the timing of the user's first menstruation based on a predetermined index calculated from the height and weight of the user The prediction device according to any one of (1) to (6) above, characterized by this (8) After the amount of change in the user's height becomes maximum and the amount of change in the user's weight becomes maximum, when the weight of the user's bones estimated from the user's height and weight satisfies a predetermined condition, the period elapsed from that time is set as the time when the user's menarche occurs. The prediction device according to (7) above, characterized in that. (9) Based on the height and the weight, the prediction unit estimates characteristics related to the growth of the user, and from the time when the amount of change in the user's height becomes maximum, the time when a period corresponding to the characteristics related to the growth of the user has elapsed is set as the time when the user's menarche occurs. The prediction device according to (7) or (8) above, characterized in that. (10) The acquisition unit further acquires information related to the psychological changes of the user as the user information. Based on the information related to the psychological changes of the user, the prediction unit predicts the time when the user's menarche occurs. The prediction device according to any one of (1) to (9) above, characterized in that. (11) The acquisition unit acquires information related to the positive psychological changes of the user among the information related to the psychological changes of the user. Based on the information related to the positive psychological changes of the user, the prediction unit predicts the time when the user's menarche occurs. The prediction device according to (10) above, characterized in that. (12) The acquisition unit acquires information related to the negative psychological changes of the user among the information related to the psychological changes of the user. Based on the information related to the negative psychological changes of the user, the prediction unit predicts the time when the user's menarche occurs. The prediction device according to (10) above, characterized in that. (13) The acquisition unit acquires user information indicating the physical characteristics of the user measured at the same time of each year. The prediction device according to any one of the above (1) to (12), characterized in that... (14) The acquisition unit acquires information regarding the secretions of the user. The prediction device according to any one of the above (1) to (13), characterized in that... (15) The acquisition unit acquires user information of a target user for whom the timing of the first menstruation is to be predicted. The prediction unit predicts the timing of the first menstruation of the target user from the user information of the target user using a model that has learned the relationship between the user information of the user and the timing of the first menstruation of the user. The prediction device according to any one of the above (1) to (14), characterized in that... (16) A provision unit that provides information according to the prediction result by the prediction unit The prediction device according to any one of the above (1) to (15), characterized by having... (17) The provision unit provides information regarding absorbent articles according to the prediction result. The prediction device according to the above (16), characterized in that... (18) The provision unit sorts out contents corresponding to the physical characteristics of the user according to the prediction result. The prediction device according to the above (16), characterized in that... (19) When the prediction result indicates that the first menstruation has started, the provision unit provides contents for managing the first menstruation and menstruation. The prediction device according to the above (18), characterized in that... (20) When the prediction result indicates that the first menstruation has not started, the provision unit provides contents for predicting the timing of the first menstruation. The prediction device according to the above (18), characterized in that... (21) An estimation unit that estimates the mode of the secondary sexual characteristics of the user based on the user information having, The providing unit provides information regarding the aspect of the secondary sexual characteristics estimated by the estimating unit. The prediction device according to (16) or (17) above, characterized in that. (22) The providing unit provides information regarding the absorbent article according to the aspect of the secondary sexual characteristics. The prediction device according to (21) above, characterized in that. (23) The predicting unit predicts the timing when the first menstruation of the user occurs based on the aspect of the secondary sexual characteristics estimated by the estimating unit. The prediction device according to (21) or (22) above, characterized in that. (24) An estimating unit that estimates the cognitive ability of the user based on the user information. The prediction device according to (16) or (17) above, having. (25) The predicting unit predicts the timing when the first menstruation of the user occurs based on the cognitive ability estimated by the estimating unit. The prediction device according to (24) above, characterized in that. (26) The providing unit provides information regarding the absorbent article according to the cognitive ability. The prediction device according to (24) above, characterized in that. (27) The providing unit provides information regarding the usage method of the absorbent article according to the cognitive ability. The prediction device according to (24) or (26) above, characterized in that. (28) When the cognitive ability is equal to or greater than a predetermined threshold, the providing unit provides information regarding the usage method of the absorbent article in which the amount of information on the usage method of the absorbent article is less than a predetermined threshold. The prediction device according to (27) above, characterized in that. (29) When the cognitive ability is less than a predetermined threshold, the providing unit provides information regarding a method of using the absorbent article, wherein the amount of information on the method of using the absorbent article is equal to or greater than a predetermined threshold. The prediction device according to (27) above, characterized in that. (30) A prediction method executed by a prediction device, an acquisition step of acquiring user information indicating physical characteristics of a user; a prediction step of predicting the timing of the user's first menstruation based on the user information A prediction method characterized by including. (31) An acquisition procedure for acquiring user information indicating physical characteristics of a user; a prediction procedure for predicting the timing of the user's first menstruation based on the user information A prediction program for causing a computer to execute.

Explanation of Signs

[0157] N Network 10 Information providing device 20 Communication unit 30 Storage unit 31 User database 32 Model database 40 Control unit 41 Learning unit 42 Acquisition unit 43 Identification unit 44 Prediction unit 45 Providing unit 100 Terminal device

Claims

1. An acquisition unit that acquires user information input into content provided to a user, the content being for inputting user information indicating the physical characteristics of the user; A prediction unit that predicts the timing of the user's menarche based on the user information; A providing unit that provides information indicating the possibility of the occurrence of each menarche at the timing of the occurrence of the menarche indicated by the prediction result of the prediction unit A prediction device characterized by comprising:

2. The acquisition unit acquires information indicating the body type of the user as the user information The prediction device according to claim 1, characterized in that:

3. The prediction unit identifies changes in the physical characteristics of the user based on the user information, and predicts the timing of the occurrence of the user's menarche based on the timing when the identified changes satisfy a predetermined condition The prediction device according to claim 1 or 2, characterized in that:

4. The prediction unit identifies the timing when the amount of change in the physical characteristics of the user is maximized, and sets the timing when a predetermined period has elapsed from the identified timing as the timing of the occurrence of the user's menarche The prediction device according to claim 3, characterized in that:

5. The acquisition unit acquires user information indicating the height of the user, The prediction unit sets the timing when a predetermined period has elapsed from the timing when the amount of change in the height of the user is maximized as the timing of the occurrence of the user's menarche The prediction device according to claim 4, characterized in that:

6. The acquisition unit acquires user information indicating the weight of the user, The prediction unit sets the timing when a predetermined period has elapsed from the timing when the amount of change in the weight of the user is maximized as the timing of the occurrence of the user's menarche The prediction device according to claim 4 or 5, characterized in that:

7. The acquisition unit acquires information indicating the height and weight of the user as the user information, The prediction unit predicts the timing of the occurrence of the user's menarche based on a predetermined index calculated from the height and weight of the user The prediction device according to any one of claims 1 to 6, characterized in that:

8. After the amount of change in the height of the user is maximized and the amount of change in the weight of the user is maximized, the prediction unit sets the timing when a predetermined period has elapsed from the timing when the weight of the bones of the user estimated from the height and weight of the user satisfies a predetermined condition as the timing of the occurrence of the user's menarche The prediction device according to claim 7, characterized in that:

9. The prediction unit estimates characteristics related to the growth of the user based on the height and the weight, and sets, as the time when the first menstruation of the user occurs, the time when a period corresponding to the characteristics related to the growth of the user has elapsed since the time when the amount of change in the height of the user becomes maximum. The prediction device according to claim 7 or 8, characterized in that.

10. The acquisition unit acquires user information indicating physical characteristics of the user measured at the same time of each year. The prediction device according to any one of claims 1 to 9, characterized in that.

11. The acquisition unit acquires information regarding secretions of the user. The prediction device according to any one of claims 1 to 10, characterized in that.

12. The acquisition unit acquires user information of a target user to be predicted for the time when the first menstruation occurs, The prediction unit predicts the time when the first menstruation of the target user occurs from the user information of the target user using a model in which the relationship between the user information of the user and the time of the first menstruation of the user is learned. The prediction device according to any one of claims 1 to 11, characterized in that.

13. The providing unit provides information regarding absorbent articles according to the prediction result. The prediction device according to any one of claims 1 to 12, characterized in that.

14. The providing unit distributes content corresponding to the physical characteristics of the user according to the prediction result. The prediction device according to any one of claims 1 to 12, characterized in that.

15. When the prediction result indicates that the first menstruation has started, the providing unit provides content for managing the first menstruation and menstruation. The prediction device according to claim 14, characterized in that.

16. When the prediction result indicates that the first menstruation has not started, the providing unit provides content for predicting the time when the first menstruation occurs. The prediction device according to claim 14, characterized in that.

17. The acquisition unit acquires, as the user information, information indicating an aspect of the secondary sexual characteristics of the user, and has The providing unit provides information regarding the aspect of the secondary sexual characteristics. The prediction device according to any one of claims 1 to 13, characterized in that.

18. The providing unit provides information regarding absorbent articles according to the aspect of the secondary sexual characteristics. The prediction device according to claim 17, characterized in that.

19. The prediction unit predicts the timing of the user's menarche based on the aspects of the secondary sexual characteristics. The prediction device according to claim 17 or 18, characterized by the above.

20. An estimation unit that estimates the cognitive ability of the user based on the user information. The prediction device according to any one of claims 1 to 13, comprising the above.

21. The prediction unit predicts the timing of the user's menarche based on the cognitive ability estimated by the estimation unit. The prediction device according to claim 20, characterized by the above.

22. The providing unit provides information about the absorbent article according to the cognitive ability. The prediction device according to claim 20, characterized by the above.

23. The providing unit provides information about the usage method of the absorbent article according to the cognitive ability. The prediction device according to claim 20 or 22, characterized by the above.

24. When the cognitive ability is equal to or higher than a predetermined threshold, the providing unit provides information about the usage method of the absorbent article, where the amount of information about the usage method is less than the predetermined threshold. The prediction device according to claim 23, characterized by the above.

25. When the cognitive ability is less than a predetermined threshold, the providing unit provides information about the usage method of the absorbent article, where the amount of information about the usage method is equal to or higher than the predetermined threshold. The prediction device according to claim 23, characterized by the above.

26. A prediction method executed by a prediction device, comprising: An acquisition step of acquiring the user information input to the content provided to the user, which is content for inputting user information indicating the physical characteristics of the user; A prediction step of predicting the timing of the user's menarche based on the user information; A providing step of providing information indicating the possibility of the occurrence of menarche at each timing of the occurrence of menarche indicated by the prediction result of the prediction step. The prediction method is characterized by including the above.

27. An acquisition procedure for acquiring the user information input to the content provided to the user, which is content for inputting user information indicating the physical characteristics of the user; A prediction procedure for predicting the timing of the user's menarche based on the user information; A providing procedure for providing information indicating the possibility of the occurrence of menarche at each timing of the occurrence of menarche indicated by the prediction result of the prediction procedure. A prediction program for causing a computer to execute the above.

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