JP2022050523A - Information output system, skin state support program, and skin state support method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information output system capable of recommending appropriate measures to a user while adjusting a load in performing the measures in response to a request from the user.

SOLUTION: An information output system includes a storage section 20, a designation load reference recognition section 14, and a measure extraction section 15. The storage section 20 stores measure information including a plurality of measures and respective loads of the plurality of measures, and a plurality of load references indicating the levels of the loads on the execution of the measures. The designation load reference recognition section 14 recognizes a designation load reference being the one load reference designated via an input section 32 among the plurality of load references. The measure extraction section 15 outputs displaying which indicates the measures within the range of the load indicated by the designation load reference to an output section 31 based on the plurality of measures and the respective loads of the plurality of measures.

SELECTED DRAWING: Figure 2

COPYRIGHT: (C)2022,JPO&INPIT

Description

The present invention relates to an information output system, a skin condition support program, and a skin condition support method.

Conventionally, various tools for skin condition care are known.

For example, in Patent Document 1, as a counseling tool used by a cosmetics salesperson or the like for a user, a skin condition explanation unit for explaining the skin condition for a typical pattern of the skin condition and a skin condition thereof are described. A counseling tool with an explanatory display of skin care methods required for the skin care method is described.

In the skin condition explanation section, the subheading "a condition that tends to lack water" as a typical pattern of the skin condition and the "barrier function that protects the skin from external stimuli" about the skin condition are also likely to deteriorate. ……… I can think of it. ”

The explanation display unit of the skin care method includes the headings "Slightly insufficient person W moisturizing" and "Insufficient person W moisturizing + lotion mask cream" as the skin care method in the skin condition.

For example, if the cosmetics salesperson determines that the customer's skin condition is slightly lacking in water, the customer's skin is recommended to perform "W moisturizing" displayed on the explanation display of the skin care method. By matching the condition with the counseling tool, it is possible to immediately present to the user measures according to the skin pattern.

Japanese Patent No. 4299080

However, in the technique of Patent Document 1, uniform advice is displayed for each skin condition. Therefore, if the burden of implementing the measures included in this advice is heavy, the user feels excessive advice, or if the burden of implementing the measures included in this advice is small, the user is unsatisfactory. You may feel it.

Therefore, the present invention provides an information output system, a skin condition support program, and a skin condition support method that can recommend appropriate measures to the user while adjusting the burden for implementing the measures according to the user's wishes. The purpose is to do.

The information output system of the present invention is
An input unit that detects user input and
An output section that outputs information and
A designated burden standard recognition unit that recognizes a designated burden standard, which is one burden standard designated via the input unit, from among a plurality of burden standards indicating the magnitude of the burden required to implement the measures that the user can tolerate.
Recognizing the degree to which the user attaches great importance to the subjective feeling of the designated state based on the user's attributes or preferences.
It is obtained by evaluating the result of the subjective evaluation of the user for the change of the designated state due to the execution of the measure and the result of the objective evaluation for the change of the designated state due to the execution of the measure according to the degree. Recognizing the effect of this measure,
The designation is based on a plurality of measures for improving the designated state, which is a skin condition, a mental state, or a physical condition, the burden of each of the plurality of measures, and the effect of each of the recognized plurality of measures. The measure extraction department that extracts measures within the range of the burden shown in the burden standard,
It is characterized by including an output control unit that outputs a display indicating the extracted measures to the output unit.

According to the information output system having the above configuration, the measure extraction unit extracts measures within the range of the burden shown in the designated burden standard based on the plurality of measures and the burdens of the plurality of measures.

The designated burden standard is a burden standard that indicates the burden on the implementation of the measures that the user can tolerate, which is designated by the designated burden standard recognition unit via the input unit.

Therefore, if the measure is within the range of the burden shown in this designated burden standard, it is highly probable that the user can tolerate it.

By outputting the information indicating the extracted measures to the output unit by the output control unit, it is possible to inform the user of the measures with a high probability of being within the range of the burden that the user can tolerate.

Therefore, according to the information output system of the present invention, it is possible to recommend appropriate measures to the user while adjusting the burden for implementing the measures according to the wishes of the user.

How to change the designated state is considered to change according to each user's attributes or preferences. According to the information output system having the configuration, the measure extraction unit recognizes the degree to which the user attaches importance to the subjective sense of the designated state based on the user's attributes or preferences. In addition, the measure extraction department evaluates the result of the user's subjective evaluation of the change in the designated state due to the execution of the measure and the result of the objective evaluation of the change in the designated state due to the execution of the measure according to the degree. The evaluation result obtained by this is recognized as the effect of the measure.

Then, the measure extraction unit extracts the measures having a relatively high effect from the measures within the range of the burden shown in the designated burden standard, and outputs the extracted measures to the output unit.

As a result, measures that are within the range of the burden that the user can tolerate and that are suitable for each of the user who wants to emphasize the subjective evaluation for the change in the specified state and the user who wants to emphasize the objective evaluation are extracted and given to the user. Recommended for.

In the information output system of the present invention
The burden standard is a burden value indicating the magnitude of the user's burden on the implementation of the measure that the user can tolerate, a time burden value indicating the magnitude of the time required to implement the measure, and the technical difficulty of the measure. It is preferable to indicate at least one upper limit value among the difficulty value indicating the above value and the psychological burden value indicating the magnitude of the psychological burden on the user in implementing the measure.

According to the information output system having the configuration, the measures are extracted after the upper limit of at least one of the time burden value, the difficulty level value and the psychological burden value of each measure is specified by the user. As a result, the time, difficulty level, and psychological burden that the user is likely to care about are suppressed, so that it is highly probable that the measures will be extracted in a form that meets the user's wishes.

In the information output system of the present invention
A designated state recognition unit that recognizes the user's designated state, and
A database that stores as time-series data indicating the time-series transition of the specified state of the recognized user is provided.
The designated burden standard recognition unit recognizes a subjective or objective target score which is a target value of the designated state based on the designated state recognized by the designated state recognition unit.
It is preferable that the output control unit outputs to the output unit a display showing the target score of the designated state and a display showing the transition of the time series of the designated state based on the time series data.

According to the information output system having the above configuration, the subjective or objective target score, which is the target value of the designated state, is recognized based on the designated state recognized by the designated state recognition unit, and the output control unit determines the target score. A display showing the target score in the designated state and a display showing the transition of the time series in the designated state are output to the output unit.

As a result, the user can be made to recognize the time-series transition of his / her designated state and the difference from the target score of the designated state based on the designated state recognized by the designated state recognition unit.

In the information output system of the present invention
The designated burden standard recognition unit includes the degree to which the user recognized based on the attributes or preferences of the user attaches importance to the subjective feeling regarding the designated state, and the designated state recognized by the designated state recognition unit. , The subjective target score and the objective target score of the designated state are recognized, and the total value of the subjective target score and the objective target score is recognized as the target score of the designated state. It is preferable to do so.

The effect of improving the designated state due to the implementation of the measures appears in both the subjective sense of the user and the objective numerical value. Then, it is assumed that which of the subjective feeling and the objective numerical value is emphasized differs depending on the user.

Therefore, by setting the target value in the designated state in consideration of whether the user attaches importance to the subjective feeling or the objective numerical value, the target value becomes more in line with the user's intention.

According to the information output system of the configuration, the degree to which the user who is recognized based on the user's attribute or preference emphasizes the subjective feeling about the designated state by the designated burden standard recognition unit and the degree of recognition by the designated state recognition unit. The subjective target score and the objective target score of the designated state are recognized based on the designated state, and the total value of the subjective target score and the objective target score is used as the target score of the designated state. Be recognized.

As a result, it is possible to present to the user a target value according to whether the user emphasizes a subjective feeling or an objective numerical value.

Information output system of the present invention In the information output system
The designated state of the user is an objective numerical value indicating a change in the designated state, a first score recognized at a predetermined time interval, and a subjective evaluation of the change in the designated state of the user. It is preferable to include a designated state recognition unit that recognizes the first score separately from the second score that is recognized at a time interval shorter than the recognition time interval.

In order to acquire the data in the specified state, for example, it is conceivable to collect and analyze the stratum corneum cells of the user's skin, but if the stratum corneum cells are collected frequently, it causes trouble and cost burden for the user. .. It can also have a negative effect on the skin.

On the other hand, if the time interval for data acquisition is too long, the information in the specified state cannot be recognized in a timely manner and notified to the user.

According to the information output system of the configuration, the designated state recognition unit recognizes the first score, which is an objective numerical value indicating the change of the designated state, at a predetermined time interval, and the time interval is shorter than the time interval. The second score, which is a numerical value indicating a subjective evaluation for the change in the designated state, is recognized.

As a result, it is possible to acquire the data in the designated state in a timely manner while suppressing the user's labor, cost burden, and influence on the designated state.

In the information output system of the present invention
A database is provided that stores the recognized first score and the second score as time-series data indicating the time-series transition of the designated state of the user.
The output control unit
Based on the first score and the second score recorded in the time series data, a display showing the transition of the time series in the designated state is configured to be output to the output unit.
When the output is performed, if the first score corresponding to the time when the second score is recognized is not included in the time series data, the first score included in the time series data is included. Or, when the estimated value of the first score at the time when the second score is recognized is recognized based on the second score, and the designated state is obtained based on the recognized estimated value and the second score. It is preferable to output a display showing the transition of the series to the output unit.

When the time interval for acquiring the first score and the time interval for acquiring the second score are different, the first score at the time when the second score is acquired does not exist (for example, the latest first score is It is assumed that it was recognized one month ago.)

According to the information output system having the above configuration, the recognized first score and second score are stored as time-series data, and the first score corresponding to the time when the second score is recognized is included in the time-series data. If not, the output control unit estimates the first score at the time when the second score is recognized based on the first score or the second score included in the time series data. Then, the output control unit outputs to the output unit a display showing the transition of the time series in the designated state based on the estimated value and the second score.

As a result, even if the corresponding first score does not exist at the time when the second score is recognized, the user can be made to recognize the score in the approximately specified state.

In the information output system of the present invention
It is preferable that the output control unit outputs a display indicating the transition of the time series in the designated state to the output unit based on the total value of the first score and the second score.

According to the information output system having this configuration, the score indicating the change in the specified state is recognized from various angles using the user's subjective evaluation and objective evaluation, but the total value is time-series for the user. Since the transition of is output, the user can intuitively recognize the change in the specified state of the user.

An explanatory diagram of the usage pattern of the skin condition support server. Configuration diagram of skin condition support server and user terminal. An explanatory diagram of a series of skin support processes by the skin condition support server. The first flowchart of the process in the skin condition support server. The second flowchart of the process in the skin condition support server. The first flowchart of the process in a user terminal. The second flowchart of the process in a user terminal. Explanatory drawing of analysis processing of initial data of skin, mind, and body by subjective data and objective data. Explanatory diagram of quantification of body condition. An explanatory diagram for quantifying the state of mind. FIG. 11A is a diagram showing the relationship between each measure and the improvement tendency of the measure, FIG. 11B is a diagram showing the schedule of each process, and FIG. 11C is a diagram showing the relationship between the subjective state and the objective state of the desired skin and skin condition. The figure which shows. An explanatory diagram of the progress table based on daily monitoring during the period when the image is displayed. An explanatory diagram of the effect of a special case on the skin condition. An explanatory diagram of a display screen of the degree of improvement of the skin condition on the user terminal. It is explanatory drawing of the evaluation method of a measure, FIG. 15A shows the evaluation standard of a measure, and FIG. 15B shows the evaluation example of a measure. It is explanatory drawing of the evaluation method of a living and a special case, FIG. 16A shows the evaluation criteria of a living and a special case, and FIG. 16B shows an evaluation example of a living and a special case. An explanatory diagram of a method for determining the degree of goal achievement. Explanatory diagram of secondary data. Questionnaire screen for estimating the ratio that emphasizes the subjective feeling of the user. Burden level selection screen. Flowchart of target score setting process. The flowchart of the decision process of the measure of 1st Embodiment. Data showing the measures of the first embodiment, the burden of the measures, and the effects of the measures. Explanatory drawing of classification of each measure in 1st Embodiment. The flowchart of the decision process of the measure of 2nd Embodiment. Data showing the measures of the second embodiment, the burden of the measures, and the effects of the measures. Explanatory drawing of classification of each measure in 2nd Embodiment. The flowchart of the decision process of the measure of 3rd Embodiment. Data showing the measures of the third embodiment, the burden of the measures, and the effects of the measures. The flowchart of the decision process of the measure of 4th Embodiment. Data showing the measures of the fourth embodiment, the burden of the measures, and the effects of the measures. Flowchart of score display processing. In the graph displayed by the score display process, FIG. 33A is a graph when the objective score from the recognition time of the previous objective score to the present time is estimated based on the previous objective score, and FIG. 33B is the previous objective score and the latest. Graph when the objective score is estimated from the time of the previous recognition of the objective score to the present time based on the objective score of.

An example of the embodiment of the present invention will be described with reference to FIGS. 1 to 18.

[A. Usage of skin condition support server]
With reference to FIG. 1, the configuration of the skin condition support server 10 and its position with respect to the system constituting the present invention will be described. The skin condition support server 10 is composed of a computer system including a CPU, a memory, various interface circuits, and the like. The skin condition support server 10 is for improving or maintaining the skin condition of a plurality of users U (Ua, Ub, Uc are exemplified in FIG. 1) by executing an image display program held in a memory on the CPU. (Image display processing) is realized.

The skin condition support server 10 performs data communication with a plurality of user U communication terminals (user terminals) 30 (30a, 30b, 30c are exemplified in FIG. 1) via a communication network 1 such as the Internet. Supports the improvement or maintenance of the skin condition of the user U. The skin condition support server 10 and the user terminal 30 constitute the "information output system" of the present invention.

The communication terminal 50 (exemplifying 50a and 50b in FIG. 1) of the person in charge T (exemplifying Ta and Tb in FIG. 1) is also connected to the communication network 1. The person in charge T obtains data including information such as an appropriate skin care method in consideration of the skin characteristics, hobbies, tastes, lifestyle, etc. of the user U via the communication terminal 50, and the skin condition support server 10 and the user terminal 30. By sending to, advice is given to the improvement of the skin condition of the user U. The communication terminal 50 of the person in charge T and the user terminal 30 of the user U do not necessarily have to be one-to-one, depending on the entire system including the skin condition support server 10, the communication terminal 50 of the person in charge T, and the communication network 1. The advice for improving the skin condition of the user U may be provided to the user terminal 30 of the user U. For example, a method of providing advice to one or a plurality of user terminals 30 of the user U by a plurality of persons in charge T via the respective communication terminals 50 may be used.

Further, the skin condition support server 10 has a function of analyzing the unique data of each user transmitted from the user terminals 30 of the plurality of users U and generating secondary data that can be used for general purposes. A service of providing the following data to another system 60 via the communication network 1 can also be performed.

[B. Skin condition support server and user terminal configuration]
The configuration of the skin condition support server 10 and the user terminal 30 will be described with reference to FIG. The skin condition support server 10 executes an image display program held in the memory on the CPU, so that the skin condition recognition unit 11, the measure group selection unit 12, the measure information transmission unit 13, the designated burden standard recognition unit 14, It functions as a measure extraction unit 15 and a secondary data generation unit 19. The processing by these configurations will be described later. Further, the skin condition support server 10 includes a support DB (database) 20 that holds various data used for image display processing of the user U. This support DB 20 is expanded on RAM, for example, and can be rewritten by updating subjective and objective data described later.

Next, the user terminal 30 of the present embodiment includes a display 31, a touch panel 32, a camera 33, a microphone 34, a CPU 35, a memory 36, and the like. The display 31 corresponds to the "output unit" of the present invention. The touch panel 32 corresponds to the "input unit" of the present invention. Instead of or in addition to this, the camera 33 or the microphone 34 of the present invention can be obtained by recognizing the user's designation based on the image of the user U captured by the camera 33 or the voice of the user U input from the microphone 34. It may function as an "input unit".

In the present embodiment, since the user terminal 30 is, for example, a smartphone, it is provided with a camera 33, a microphone 34, and the like. Alternatively, a professional imaging device may be used. The CPU 35 executes the program of the image display application 35a (hereinafter referred to as the skin support application 35a) held in the memory 36, so that the user U can support the skin condition support server 10 via the skin support application 35a. It will be in a state where it can be enjoyed. The CPU 35 that executes the skin support application 35a corresponds to the "first information output control unit" and "second information output control unit" of the present invention.

In addition, the user U separately has a keratin collecting tape 37 (exemplifying 37a, 37b, 37c in FIG. 1) for acquiring skin cells. The keratin collecting tape 37 may be provided to the user U by the person in charge T in advance, or the user U may purchase a commercially available keratin collecting tape 37.

In the following description, for convenience of explanation, the user who is the target of the support process for improving or maintaining the skin condition is referred to as user Ua, and the user different from "user Ua" is referred to as "other user Ub, Uc". ..

[C. A series of processes by the skin condition support server]
Next, a series of processes by the skin condition support server will be described with reference to FIG. The skin condition support server 10 includes "1. goal setting", "2. schedule determination", "3. monitoring", "4. schedule correction", and [5. The processing of each step of [Goal determination] and “6.2 Secondary data generation” is executed according to the flowcharts shown in FIGS. 4 and 5. Further, the user terminal 30 executes the processing according to the flowchart shown in FIGS. 6 and 7 according to the processing by the skin condition support server 10 in each process. Hereinafter, the processing of the CPU 35 of the skin condition support server 10 and the user terminal 30 in each step will be described with reference to the flowcharts shown in FIGS. 4 to 7.

In STEP 50 of FIG. 6, the user Ua downloads the program of the skin support application 35a to the user terminal 30 and activates the skin support application 35a. Then, the user Ua applies for registration to the skin support application 35a.

When the skin condition support server 10 receives the registration application from the user Ua in STEP 10 of FIG. 4, it recognizes that "the registration application from the user Ua has been accepted" and proceeds to STEP 11. Then, the image display process after STEP 11 is started.

[D. Goal setting process]
The process of "1. Goal setting" shown in FIG. 3 is executed by the skin condition recognition unit 11 and the measure group selection unit 12. In STEP 11 of FIG. 4, the measure group selection unit 12 prompts the user terminal 30 to input information for grasping the current skin, body, and mental states of the user Ua and the skin condition requested by the user Ua. Send the data.

In the user terminal 30 that has received the initial information request data, the skin support application 35a, in STEP 51 of FIG. 6, gives the user Ua the current skin, body, and mental states, and the skin condition requested by the user Ua. A screen prompting the input of is displayed on the display 31. On the other hand, the user terminal 30 transmits the initial user information data including the information input by the user Ua to the skin condition support server 10.

In STEP 11 of FIG. 4, the skin condition recognition unit 11 receives the initial user information data and recognizes the skin, mind, and body states of the user Ua from the initial user information data, and the skin condition requested by the user Ua. Based on, set the target score (goal) of the skin condition.

Here, the initial user information data includes subjective data and objective data regarding the skin condition, the physical condition, and the mental condition. Although detailed definitions will be described later, subjective data is items judged by the user's subjectivity, and objective data is data based on inspection results, image analysis, and factual information. The subjective data of the skin condition is data showing, for example, the degree of satisfaction of the user Ua with respect to the current skin condition in 10 stages. The objective data of the skin condition is the skin image data of the user Ua. In addition to the objective data of the skin condition included in the initial user information data, the objective data of the skin condition may include the analysis data of the stratum corneum cells of the user Ua collected by the keratin collection tape 37. The analysis data of the stratum corneum cells are specifically, for example, data on water retention capacity and sebum eligibility. In this case, the stratum corneum cells are analyzed by, for example, a measuring device 45 connected to the user terminal 30, or the image data of the stratum corneum collection tape 37 is transmitted from the user terminal 30 to the skin condition support server 10. The image of the keratin collecting tape 37 may be analyzed on the skin condition support server 10 side to measure the water retention capacity, sebum eligibility, and the like.

The satisfaction level of the user Ua is acquired by inputting a questionnaire in the skin support application 35a. Further, the skin image data is image data acquired by the user Ua taking an image of the user Ua's face by an external camera connected to the camera 33 of the user terminal 30 or the connection terminal 40.

Further, the skin support application 35a displays the usage method of the keratin collecting tape 37 on the display 31 to the user Ua, and urges the user Ua to use the keratin collecting tape 37 and to mail it separately. The skin support application 35a may urge the user Ua to use the keratin collecting tape 37 and capture a skin image so that the captured image is transmitted to the skin condition support server 10.

As shown in FIG. 8, the skin condition recognition unit 11 sets the initial value of the skin condition, for example, the subjective score of 3, the skin image score of 3, the water retention capacity score of 2, and the sebum eligibility score. Allocate to 1 and use the total value as the skin condition score. The score may be expressed as a decimal number or a negative number instead of a positive integer. The total value of the skin image score, the water retention capacity score, and the sebum eligibility score is hereinafter appropriately referred to as "objective score". The objective score may be a skin condition score (numerical value) determined based on objective data, and is, for example, measured by a user's skin moisture content and sebum content meter measured by a stratum corneum moisture meter. It may be the amount of sebum on the user's skin or a value determined based on these. The objective score may be an average value, a maximum value, a minimum value, or a minimum value of a skin image score, a water retention capacity score, and a sebum eligibility score.

Recognition of the water retention capacity score and the sebum eligibility score by analysis of the stratum corneum cells is called the first recognition method. The first recognition method is at least one of a method of measuring the water content of the user's skin with a stratum corneum moisture meter and a method of measuring the sebum content of the user's skin with a sebum meter. including. Further, in order to periodically recognize the user's skin by the first recognition method, the skin condition recognition unit 11 periodically sends a message urging the user terminal 30 to use the keratin collecting tape 37 or the like. To encourage the user to take action.
At this time, "regular" does not have to be strictly equidistant in time, and may be equidistant as long as the skin condition is not affected. For example, when the first recognition method is implemented every three months, if the first recognition method is implemented on January 1, not only April 1 just three months later, but also March one week before that, for example. A message may be sent to the user terminal 30 around 24 days, or for example, a message may be sent to the user terminal 30 around April 8 one week later. In addition, when providing services over the long term, for example, when you want to investigate minor improvements, set the first recognition method every month, and every three months to investigate the effect of seasonal changes on the skin condition. The recognition timing can be changed, such as by setting the first recognition method.

Each of the recognition of the subjective score based on the subjective data of the skin condition by the input of the questionnaire and the recognition of the skin image score based on the skin image data of the user Ua is referred to as the second recognition method. As the second recognition method, the skin condition of the user Ua may be recognized by either the recognition of the subjective score based on the subjective data of the skin condition by the input of the questionnaire and the recognition of the skin image score based on the skin image data of the user Ua. , Different methods may be included. Moreover, the second recognition method is performed more frequently than the first recognition method. This is because the use and mailing of the keratin collecting tape 37 is troublesome, complicated, and expensive. Further, if the keratin collecting tape 37 is frequently used, the skin of the user Ua may be adversely affected.

For example, the first recognition method is carried out every three months, and the second recognition method is carried out every day. Further, when the timings of the first recognition method and the second recognition method overlap, it is preferable that the first recognition method is carried out at the same timing, because accurate data can be obtained. However, the present invention can be implemented and the effect can be obtained even if the second recognition method is not implemented when the first recognition method is implemented.

The subjective score may be any score determined based on the subjective data.

The subjective data and the objective data of the physical condition are separated as shown in FIG. The detailed definition will be described later, but like the subjective data and objective data of the skin, the subjective data of the physical condition is the item judged by the subjectivity of the user Ua, and the objective data is the data based on the inspection result, the image analysis, and the fact information. Is. The subjective data of the physical condition is acquired by the user Ua inputting a questionnaire through the skin support application 35a. The objective data of the physical condition was measured by the image data of the tongue and lips of the user Ua captured by the user Ua using the camera 33 of the user terminal 30, and the measuring device 45 connected to the connection terminal 40 of the user terminal 30. It is the measurement data of the blood pressure, the arrhythmia, the urinary component, the blood component, etc. of the user Ua, and the data such as the number of times of poor physical condition such as headache or stiff shoulder, the degree of fatigue determination, etc. acquired by the questionnaire input in the skin support application 35a. In preparation for future development of services other than skin care, information on the occurrence of various diseases may be included in the initial user information data.

The subjective data and the objective data of the mental state are separated as shown in FIG. The detailed definition will be described later, but like the subjective data and objective data of the skin, the subjective data of the mental state is an item judged by the subjectivity of the user Ua, and the objective data of the mental state is used for inspection results, image analysis, and fact information. Based on the data. The subjective data is acquired by inputting a questionnaire in the skin support application 35a. The objective data is acquired by inputting a questionnaire (frequency of laughing in a day, etc.) in the skin support application 35a and measuring with a measuring device (estimating the psychological state from pulse monitoring, etc.). In preparation for the development of services other than skin care in the future, information on the occurrence of various mental illnesses may be included in the initial user information data.

The skin condition recognition unit 11 stores the subjective data and objective data of the recognized user Ua's skin, body, and mental state in the support DB 20.

The skin condition recognition unit 11 is as shown by the triangle on the right side of FIG. 8 based on the subjective data and the objective data of the user Ua's skin condition, body condition, and mental state recognized from the initial user information data in this way. The initial values of the three axes representing the skin condition as 1 to 9, the physical condition as 1 to 6, and the mental condition as 1 to 6 are set. Similar to the skin condition score, the physical condition or mental condition subjective score and objective score are calculated from the subjective data and objective data of the physical condition or mental condition, and the physical condition score and the mental condition score are calculated based on them. May be treated as.

Further, the measure group selection unit 12 acquires "measure category, hope, frequency", "current measure", and "desired skin and score" included in the initial user information data. The "measure category, hope, frequency", "current measure" and "desired skin and score" are input by the user Ua by the skin support application 35a. In addition to these, the measure group selection unit 12 may acquire "the body and score that one wants to be" and "the mind and score that one wants to be".

Here, in "skin and score that you want to become", "skin that you want to become" means improvement of dryness, stiffness, sensitivity of skin, acne, blemishes, spots, wrinkles, sagging, dullness, and dark circles. It is a target for improving skin condition selected from improvement of complexion, improvement of firmness, and the like. The "score" is the degree of satisfaction of the user Ua with respect to the skin condition of each target, and is a score selected by the user in 10 steps from 1 to 10 in the skin support application.

The support DB 20 stores the improvement tendency of the subjective state and the improvement tendency of the objective state of the skin condition associated with each improvement target. For example, as shown in FIG. 11C, "improvement of dryness" includes minimizing the difference between the subjective condition of skin condition "improvement of dryness" and the standard of objective condition of skin condition "water retention capacity and sebum eligibility". Is associated with.

For example, when the "desired skin" is "improvement of dryness" and the satisfaction score of the dryness of the current skin condition is 3, it is associated with "improvement of dryness" according to the selection of the user Ua. Satisfaction level 5 for the subjective state "improvement of dryness" of the skin condition of the user Ua is set as a subjective target score.

In addition, the measure group selection unit 12 sets an objective improvement target for the skin condition associated with "improvement of dryness". For example, the measure group selection unit 12 determines the skin condition of the user Ua based on the criterion "minimize the difference between the water retention capacity and the sebum eligibility" associated with "improvement of dryness" according to the selection of the user Ua. Of these, a sebum eligibility value of 2, which is lower than the water retention capacity, is set as an objective target score.

The process of setting the target score according to the selection of the user Ua will be described later.

In addition, in the "category of measures, hope, frequency", the category is "dietary habits, behavior at home, exercise, how to use cosmetics", etc., and the hope is "difficulty, time constraints, scenes of skin care", etc. As the frequency, "the number of times to receive advice per day" or the like is selected.

The "currently implemented measure" is a measure already taken by the user Ua, and is represented by the content, frequency, or degree of "immersing in a bathtub" or the like.

[E. Schedule determination process]
The process of "2. Schedule determination" shown in FIG. 3 is executed by the measure group selection unit 12 and the measure information transmission unit 13. The measure group selection unit 12 selects a measure group for achieving a goal (subjective target score and objective target score) in STEP 12 of FIG. This selection is made in consideration of the improvement tendency of the subjective state of the skin condition, the improvement tendency of the objective state of the skin condition, and the suitable surrounding environment associated with each of the above-mentioned improvement targets. The measure group selection unit 12 determines the temperature, humidity, etc. of the surrounding environment of the user Ua during the schedule period based on the position information detected by the area or GPS sensor registered in advance and the date and time acquired from the clock function of the terminal. Predict.

For example, in the measure group selection unit 12, the category hope is "behavior at home, eating habits, exercise", and the humidity is predicted to be 50% on average like the rainy season, which is a subjective goal. When the score is a satisfaction level of 5 or more for "dryness" and the objective target score is sebum eligibility 2 or more, the improvement tendency of the subjective state includes "improvement of dryness" and the improvement tendency of the objective state is "sebum eligibility". Select a measure that includes "improvement of sex" and is one of "behavior at home, eating habits, exercise" in the category, and the suitable surrounding environment does not contradict the humidity of 50%.

Here, the improvement tendency of the subjective state and the improvement tendency of the objective state may be determined in advance by an expert such as the person in charge T, or may be implemented by other users Ub and Uc stored in the support DB 20. It may be an improvement tendency of the subjective state and an improvement tendency of the objective state estimated based on the measures taken and the time-series change of the skin condition of other users Ub and Uc, or the measures taken and the skin condition of the user Ua. When the time-series change of is stored in the support DB 20, it may be an improvement tendency of the subjective state and an improvement tendency of the objective state estimated based on the information.

For example, in the support DB 20, the measures implemented by each of the other users Ub and Uc, the time-series changes in the subjective data of the skin conditions of the other users Ub and Uc before and after the measures are implemented, and the other users. One or both of the time-series changes in the objective data of the Ub and Uc skin conditions are stored.

Further, for example, in the support DB 20, the measure "Take a bath" implemented by each of the other users Ub and Uc and the subjective state of the skin condition of each of the other users Ub and Uc before and after the measure is implemented. It is assumed that "satisfaction with the feeling of dryness" as a time-series change is memorized.

At this time, the measure group selection unit 12 determines the subjective data (dryness) of the skin condition on the day before the bath and the day when the bath is used, for example, regarding the measure "immerse in the bath" for each other user Ub and Uc. Satisfaction with) is calculated. Then, the measure group selection unit 12 takes the average value of the change amount of the average value of the change amount of the satisfaction degree about the dry feeling for each other user Ub and Uc. For example, when the average value of the change amount of the "satisfaction with the feeling of dryness" is equal to or more than the predetermined value, the measure group selection unit 12 "improves the feeling of dryness" for the improvement tendency of the subjective state of the measure "immerse in the bathtub". Recognize that. The improvement tendency of the objective state can be recognized in the same way as the improvement tendency of the subjective state.

The measure group selection unit 12 may narrow down the range of other users Ub and Uc to be processed, such as the same age group and the same skin condition, based on the age and skin condition of the user Ua.

Further, when the measure implemented in the support DB and the time-series change of the skin condition of the user Ua are stored in the measure group selection unit 12, the measure group selection unit 12 is estimated based on the information calculated in the same manner as above. You may recognize the improvement tendency of the subjective state and the improvement tendency of the objective state.

In the first schedule determination process of the user Ua, the measure group selection unit 12 recognizes the improvement tendency of the subjective state and the improvement tendency of the objective state from the subjective data and the objective data of the skin condition of other users Ub and Uc. However, in the second schedule determination step of the user Ua, the improvement tendency of the subjective state and the improvement tendency of the objective state may be recognized from the subjective data and the objective data of the skin condition of the user Ua.

The measure group selection unit 12 recognizes the improvement tendency of the subjective state and the improvement tendency of the objective state not only for the skin state but also for the mental state and the physical state, and the improvement tendency of the subjective state of the mental state and the physical state and the improvement tendency of the physical state. Measures may be selected in consideration of the tendency of improvement in the objective state.

The measure group selection unit 12 may exclude measures having the same content and frequency or the same degree as the “current measures” from the measure group. This is because it is not necessary to propose the measures that the user has already taken.

In the example of FIG. 11A, the measure group selection unit 12 selects a measure group that is a combination of a plurality of measures so as to include "take a bath", "vitamin C intake", "vegetable intake", and "walk 10,000 steps or more". ..

The measure information transmission unit 13 evaluates the priority of the measure according to the "category, hope, frequency" of the user Ua and the input from the measure group, and determines the initial measure according to the priority.

The evaluation of the priority of the measure and the determination process of the initial measure according to the priority will be described later.

FIG. 12 shows an example of a schedule in which "take a bath", "vegetable intake", and "walk 10,000 steps or more" are selected as initial measures. The measure information transmission unit 13 transmits schedule data indicating the contents of the schedule determined in this way to the user terminal 30.

The measure information transmission unit 13 also creates a plan for implementing each process for a certain period based on the designation of the user Ua. In FIG. 11B, goals are set and schedules are determined at START, daily monitoring is performed, schedules are revised weekly, a progress graph is created one month later, goal judgments and new goals are determined in the third month. A plan for a series of events to configure is shown. In addition to or in place of the user Ua's designation, the measure information transmission unit 13 may use a predetermined plan for implementing each process for a certain period of time.

When the schedule data is received from the skin condition support server 10 in STEP 52 of FIG. 6 on the user terminal 30, the skin support application 35a has the schedule execution table as shown in FIG. 12 and the work contents as shown in FIG. 11B. The plan can be displayed to encourage the user Ua to implement each measure. In the execution table of the schedule of FIG. 12, the contents of each measure (“take a bath”, “vegetable intake”, “walk 10,000 steps or more”) are displayed.

[F. Monitoring process]
The process of "3. Monitoring" shown in FIG. 3 is executed by the skin condition recognition unit 11 and the measure information transmission unit 13 every period set by the user Ua on the skin support application 35a (every day in FIG. 11B). .. The user Ua who has started to use the skin support application 35a uses the user terminal 30 to check the daily skin, body, and mental states, the implementation status of the measures instructed by the schedule, and the users other than the measures instructed by the schedule. Enter the implementation status of Ua's voluntary actions (actions outside the policy). In addition to information indicating whether or not "take a bath", "ingestion of vegetables", and "walking 10,000 steps or more" have been implemented, "30 minutes", "take a bath", and "300g" It includes the degree of implementation of measures such as "ingestion of vegetables", "15,000 steps" and "walking", which are expressed in terms of time and amount.

When the skin, body, and mental state are input by the user Ua in STEP 53 of FIG. 6, the skin support application 35a proceeds to STEP 60, and similarly to the above-mentioned initial user information data, the skin, body, and skin of the user Ua. The current user information data including subjective data and objective data about the state of mind is transmitted to the skin condition support server 10 and the process proceeds to STEP 54. The skin support application 35a proceeds to STEP 54 as it is when the skin, body, and mental states are not input by the user Ua in STEP 53 of FIG. The data transmitted here does not include data on stratum corneum cells collected by the stratum corneum collection tape 37.

Further, the skin support application 35a advances the process to STEP 61 when the schedule execution status (execution status of each measure) is input by the user Ua in STEP 54 of FIG. 6, and displays the execution status data indicating the schedule execution status. It is transmitted to the skin condition support server 10 and the process proceeds to STEP 55 in FIG. When the schedule execution status (execution status of each measure) is not input by the user Ua in STEP 54 of FIG. 6, the skin support application 35a proceeds to STEP 55 as it is.

Further, the skin support application 35a proceeds to STEP 62 when the implementation status of the non-measure action is input by the user Ua in STEP 55 of FIG. 7, and the non-measure action implementation data showing the content of the implemented non-measure action is shown. Is transmitted to the skin condition support server 10 and the process proceeds to STEP56. The skin support application 35a proceeds to STEP 56 as it is when the implementation status of the non-measure action is not input by the user Ua in STEP 55 of FIG. 7.

STEP13 to STEP16 in FIG. 4 and STEP20 to STEP22 in FIG. 4 are processes by the measure information transmission unit 13. When the skin condition recognition unit 11 receives the current user information data from the user terminal 30 in STEP 13, the process proceeds to STEP 20, the current user information data is accumulated in the support DB 20, and the process proceeds to STEP 14. When the skin condition recognition unit 11 does not receive the current user information data from the user terminal 30 in STEP 13, the skin condition recognition unit 11 proceeds to the process as it is in STEP 14.

Further, the measure information transmission unit 13 proceeds with processing in STEP 21 when the execution status data is received from the user terminal 30 in STEP 14, stores the execution status data in the support DB 20, and proceeds with processing in STEP 15. On the other hand, if it is determined in STEP 14 that the execution status data has not been received from the user terminal 30, the process proceeds to STEP 15 as it is.

Further, the measure information transmission unit 13 proceeds to STEP 22 when receiving the non-measure action implementation data from the user terminal 30 in STEP 15, stores the non-measure action implementation data in the support DB 20, and processes it in STEP 16 of FIG. Proceed. On the other hand, when the measure information transmission unit 13 does not receive the non-measure action implementation data from the user terminal 30 in STEP 15, the process proceeds to STEP 16 of FIG. 5 as it is.

Moving to FIG. 5, in STEP 16, the measure information transmission unit 13 is based on the initial user information data of the user Ua, the current user information data, the execution status data, the non-measure action implementation data, etc. accumulated in the support DB 20. Progress table data indicating the progress status of the schedule is created, and this progress table data is transmitted to the user terminal 30.

Here, as shown in FIG. 12, for example, the progress table of the schedule shows the score of the skin condition (here, dry skin), the score of the physical condition, the score of the mental condition, and the measures (ingestion of the bathtub, vegetables) in order from the top. The implementation status (ingestion, walking 10,000 steps or more), living information (vegetable intake, water intake), and special living cases are displayed on a daily basis.

In addition, the schedule progress table includes the degree of implementation of the measures ("30 minutes" bathtub, "300 g" vegetable intake, "15,000 steps" walking).

In the user terminal 30, when the skin support application 35a receives the progress table data transmitted from the skin condition support server 10 in STEP 56 of FIG. 7, the process proceeds to STEP 63 and the progress table data is held in the memory 36. The skin support application 35a displays the progress table shown in FIG. 12 on the display 31 of the user terminal 30 by using the progress table data stored in the memory 36.

Further, in addition to the progress table data, the skin support application 35a has the initial user information data, the current user information data, and the execution status data of the user Ua stored in the support DB 20 of the skin condition support server 10 recognized via communication. , Information indicating the transition or change of each state of the skin, body, and mind of the user Ua is displayed on the display 31 of the user terminal 30 by using the non-measure action implementation data or the like.

For example, as shown in FIG. 13, the skin support application 35a includes the user's behavior (change of face washing method, massage, etc.) and the user's physical condition (physiology, lack of sleep, etc.) other than the measures according to the schedule. , The relationship between changes in the skin condition of the user Ua is displayed on the display 31 as a daily time-series graph.

In addition, as shown in FIG. 14, the skin support application 35a changes the skin condition including the keratin state of the user Ua, the psychological condition, the satisfaction level of skin care, and the evaluation value of how to use the cosmetics on a monthly basis. The contrasted radar chart is displayed on the display 31.

The user Ua visually recognizes these displays by the skin support application 35a and confirms the change in each state of his / her skin, body, and mind, thereby grasping the change in the state of body and mind as well as the degree of improvement of the skin. Therefore, it is possible to reach the goal of the target skin condition while improving the skin, body, and mind condition in a well-balanced manner.

Further, the skin support application 35a proceeds to STEP64 after STEP63, and executes the score display process shown in FIG. The details of the score display process will be described later.

[G. Schedule correction]
The process of "4. Schedule correction" shown in FIG. 3 is executed by the measure information transmission unit 13 every period set by the user Ua on the skin support application 35a (every week in FIG. 11B). STEP17 to STEP20 and STEP30 to STEP33 in FIG. 5 are processes by the measure information transmission unit 13.

In STEP 17, the measure information transmission unit 13 is incorporated into the target achievement degree and schedule of the user Ua skin condition based on the initial user information data, the current user information data, the execution status data, etc. of the user Ua accumulated in the support DB 20. Evaluate the degree of implementation of each measure and the effect of each measure.

The measure information transmission unit 13 extracts the correlation between the skin condition and the physical or mental condition using the evaluation criteria of the measures shown in FIG. 15A, and based on this correlation, each measure incorporated in the schedule. Judgment of continuation, exclusion from the measure group, cancellation of the measure, change to another measure.

In the evaluation criteria of FIG. 15A, four items are used as judgment items: presence / absence of implementation, effect on skin, effect on body, and effect on mind, and the implementation rate exceeds the predetermined implementation rate, which has a positive effect on the skin. Measures that are present and that do not have a negative effect on the body and mind are evaluated as A and are judged to be continued. In addition, in FIG. 15A, the measure whose implementation rate exceeds the predetermined implementation rate is described as "implementation", and the measure whose implementation rate is less than or equal to the predetermined implementation rate is described as "non-implementation". The same applies to FIGS. 12 and 15B.

When the timing of the impact of the measure and the period for which the impact continues are set for each measure, the measure information transmission unit 13 determines the impact of each measure based on the timing of the impact of the measure and the period during which the effect of the measure continues. You may judge.

For example, if it is stipulated that the effect of the measure of "immersing in a bathtub" on the skin, the body, and the mind will be affected the next day and will continue for only one day, the measure information transmission unit 13 will For example, it is judged that the influence of the measure of "immersing in a bathtub" on December 15 is reflected in each state on December 16.

In addition, if it is stipulated that the effect of the measure of "vegetable intake" on the skin, the body, and the mind will be affected after one week and will continue for only three days, the measure information transmission unit 13 will be notified. For example, it is judged that the influence of the measure of "vegetable intake" on December 15 is reflected in each state from December 22 to December 24.

On the other hand, measures that are implemented and have a positive effect on the skin but have a negative effect on either the body or the mind are evaluated as B and are judged to be canceled or changed to another measure. In addition, since it is considered that the measure whose implementation rate is less than the predetermined implementation rate has a heavy load on the user Ua, it is evaluated as C and canceled or another measure (for example, a measure to reduce the load on the user Ua or another measure). Measure) is judged to be a change.

The measure information transmission unit 13 may evaluate whether each measure has a positive or negative effect on the skin, body, and mind by implementing each measure for only one day, or in a certain period such as several days or several weeks. By implementing each measure, it may be evaluated whether it has a positive or negative effect on the skin, body and mind. When the evaluation is performed in a certain period, for example, the measure information transmission unit 13 gives a B evaluation when any of the states is adversely affected at a certain ratio, a C evaluation when the implementation ratio is below a certain ratio, and other cases. In the case of, it may be evaluated as A. Instead of this, the measure information transmission unit 13 may be evaluated as B when, for example, the average value of satisfaction in any of the states in a certain period is equal to or less than a predetermined value. In addition, if the satisfaction level of any of the states in one day is less than or equal to the predetermined value and the average value of the satisfaction levels of any of the states in a certain period is less than or equal to the predetermined value, the evaluation is C and any of the evaluations in one day. If the satisfaction level of one of the states is below the specified level, or if the average value of the satisfaction level of any of the states is below the specified level, the rating is B, and the satisfaction level of any of the states in one day is specified. If the value is exceeded and the average value of satisfaction in any of the states exceeds a predetermined value, the evaluation may be A, and the evaluation for one day and the evaluation for a certain period may be used in combination. ..

Further, when the improvement degree of the skin condition score shown in FIG. 8 is equal to or less than the predetermined improvement degree, the measure information transmission unit 13 implements a measure in which the improvement degree of the skin condition score is equal to or less than the predetermined improvement degree. It may be excluded from the measure group. The measure information transmission unit 13 sets a measure group in which the improvement degree of the physical condition or the mental state score is less than or equal to the predetermined improvement degree when the improvement degree of the physical condition or the mental state score is less than or equal to the predetermined improvement degree. May be excluded from.

FIG. 15B shows an example in which the evaluation criteria shown in FIG. 15A are applied to the measures in the present embodiment (soaking in a bathtub, ingesting vegetables, walking 10,000 steps or more). According to FIG. 15B, the measure information transmission unit 13 decides to continue on the next schedule with "use in the bathtub" as an A evaluation, and excludes "vegetable intake" from the measure group as a B evaluation. Decided to cancel or change to another measure on the schedule, and "walk 10,000 steps or more" is evaluated as C, excluded from the measure group, canceled on the next schedule or changed to another measure. I have decided.

The measure information transmission unit 13 determines the influence of a plurality of measures for each combination of those measures. For example, if the combination of "soak in the bathtub" and "vegetable intake" is B evaluation or C evaluation, the measure information transmission unit 13 decides only one measure of "soak in the bathtub" or "vegetable intake". , Or it may be changed to be a combination of any of these measures and another measure.

The measure information transmission unit 13 performs such an evaluation process, determines the necessity of schedule modification (mainly modification by changing to other measures of the measure group), and when it is determined that schedule modification is necessary, processes it in STEP30. To correct the schedule. Then, the schedule correction data, which is the data of the corrected schedule, is transmitted to the user terminal 30, and the ST
Proceed to EP19. On the other hand, when it is determined that the schedule revision is unnecessary, the measure information transmission unit 13 proceeds from STEP 18 in FIG. 5 to STEP 19 in FIG. 5, and in this case, the schedule is not revised.

Next, the measure information transmission unit 13 is incorporated in each non-measure action (scheduled) performed by the user Ua based on the initial user information data, the current user information data, the non-measure action implementation data, and the like in STEP 19. In addition to the measures, the actions taken by the user) are evaluated.

The measure information transmission unit 13 determines whether or not to recommend or prohibit the non-measure action by using the evaluation criteria of the non-measure action shown in FIG. 16A. In the evaluation criteria of FIG. 16A, the influence on each state of the skin, body, and mind is used as a determination item.

If "there is a positive effect on the skin, body, or mind, and there is no negative effect on any of them," a D rating is recommended. On the other hand, if "it has a bad effect on the skin, body, or mind", it will be evaluated as E and prohibited. In addition, if "there is no effect on the skin, body, or mind", it will be evaluated as F and implementation is not recommended.

FIG. 16B shows an example in which the evaluation criteria shown in FIG. 16A are applied to the out-of-measure behavior (massage received, ingested a large amount of chocolate) in the present embodiment. According to FIG. 16B, the measure information transmission unit 13 has decided to recommend the implementation according to the following schedule as a D evaluation for "receive a massage". In addition, regarding "large amount of chocolate intake", as an E evaluation, it has been decided to propose measures to stop it in the next schedule (for example, alternatives to ingesting Japanese sweets).

When the measure information transmission unit 13 decides to recommend or prohibit the implementation of the measures incorporated in the schedule, such as cancellation or change, or actions outside the measures, the process proceeds from STEP 20 to STEP 31. Then, when the recommendation is decided, the process proceeds from STEP 31 to STEP 33, the non-measure action recommendation data for recommending the implementation of the non-measure action is transmitted to the user terminal 30, and the process proceeds to STEP 13 in FIG.

On the other hand, when the measure information transmission unit 13 decides the prohibition proposal, the process proceeds from STEP 31 to STEP 32, and the non-measure action prohibition data proposing the prohibition of the non-measure action is transmitted to the user terminal 30, and FIG. Proceed to STEP13.

Further, the measure information transmission unit 13 proceeds from STEP 20 to STEP 13 of FIG. 4 when there is no action outside the measure that proposes recommendation or prohibition. If there is an alternative action in the non-measure action that proposes prohibition, the non-measure action prohibition data that proposes a change to the alternative action may be transmitted to the user terminal 30 instead of the prohibition proposal.

When the skin support application 35a receives the schedule correction data from the skin condition support server 10 in STEP 57 of FIG. 7, the skin support application 35a proceeds to STEP 65 and corrects the schedule based on the schedule correction data. Then, the skin support application 35a updates the schedule data held in the memory 36, and advances the process to STEP 58.

Further, when the skin support application 35a receives the non-measure action recommendation data or the non-measure action prohibition data from the skin condition support server 10 in STEP 58 of FIG. 7, the process proceeds to STEP 66, and the non-measure action is performed according to the received data. A screen for notifying a proposal for recommending or prohibiting an action is displayed on the display 31 of the user terminal 30. Note that this notification may be performed by displaying a notification message on the progress table shown in FIG. 12, for example. In addition, the schedule may be revised as a new measure for the recommended non-measure action.

[H. Goal judgment process]
In the process of "5. Goal determination" shown in FIG. 3, every period set by the user Ua on the skin support application 35a (3 months after START in FIG. 11B), the skin condition recognition unit 11 and the measure group It is executed by the selection unit 12 and the measure information transmission unit 13.

The skin support application 35a displays a message prompting the use of the keratin collecting tape 37 and the mailing of the keratin collecting tape 37 on the display 31 of the user terminal 30.

The skin condition recognition unit 11 recognizes objective values of skin condition (water retention capacity, sebum eligibility, etc.) based on the information obtained from the mailed keratin collection tape 37.

In addition, the skin support application 35a displays a message prompting the use of a questionnaire response and imaging of the skin or the like on the display 31 of the user terminal 30, and transmits the obtained information.

The skin condition recognition unit 11 recognizes the subjective value (subjective score) of the dryness of the skin and the objective value (skin image score) of the skin condition based on the information obtained from the skin support application 35a.

The measure group selection unit 12 and the measure information transmission unit 13 compare the evaluation values at the start of support for the skin condition and after 3 months based on the subjective value of the dryness of the skin and the objective value of the skin condition. Determine the degree of goal achievement.

In the example of FIG. 17, since the score of the subjective value of dryness increased from 3 to 5 in 3 months, it was judged to be achieved (○), and as for the objective value, the skin image score was 3 to 4 in 3 months. It is judged to be achieved (◯) because the water retention capacity is maintained at 2 and the sebum eligibility is increased from 1 to 2. Since both the subjective value and the objective value have achieved the goal, it is judged that the goal has been achieved as a whole.

The skin condition recognition unit 11 and the measure group selection unit 12 re-execute the process of "1. Goal setting" shown in FIG. 3 in order to set a new goal when the goal is achieved. If the goal is not reached, the skin condition recognition unit 11 and the measure group selection unit 12 may carry out the "2. schedule determination" process, or "1. goal setting" according to the user's wishes or progress. The process may be performed again.

[I. Secondary data generation]
The process of "6.2 Secondary data generation" shown in FIG. 3 is executed by the secondary data generation unit 19. The secondary data generation unit 19 includes various data such as initial user information data, stratum corneum cell analysis data, current user information data, execution status data, and out-of-measure action implementation data transmitted from a plurality of users U (hereinafter, individual users). Data) is sequentially accumulated in the support DB 20 for each user.

Then, the secondary data generation unit 19 analyzes the user individual data stored in the support DB 20, and as shown in FIG. 18, for example, the characteristics (gender, age, place of residence, preference, lifestyle, etc.) of each user. ), Support improvement targets (dryness, stiffness, sensitivity, acne, deflation, etc.), measures proposed by the schedule (soaking in a bathtub, eating vegetables, walking 10,000 steps or more, etc.), and skin by implementing the measures, Generates secondary data that associates changes in each state of the body and mind.

In addition, as for the non-measure behavior, the secondary data generation unit 19 generates secondary data in which the characteristics of each user and the influence of each state of the skin, body, and mind due to the implementation of the non-measure behavior are associated with each other, as in FIG. Generate.

The secondary data generated in this way is effectively utilized when selecting effective measures for improving the skin condition while having a positive effect on the body and mind for users having similar characteristics. be able to. For example, in the process of “2. Schedule determination” in FIG. 3 described above, the measure group selection unit 12 can select a measure suitable for the characteristics of the user Ua by referring to the secondary data.

Further, in the process of "4. Schedule correction" in FIG. 3 described above, when the measure information transmission unit 13 changes the schedule according to the transition of each state of the skin, body, and mind of the user Ua, the secondary data You can change to a schedule that incorporates more effective measures or actions outside the measures by referring to.

Furthermore, the secondary data can be effectively used to support the skin condition, and for marketing purposes targeting users with certain characteristics (for example, outdoor-oriented women in their 30s living in Tokyo). Can also be used. Therefore, the secondary data may be provided to another system 60 or the like shown in FIG.

[J. Target score setting process]
A target score setting process executed in the series of processes of STEP 11 of FIG. 4 will be described with reference to FIGS. 19 to 21. The target score setting process is a process executed by the designated burden standard recognition unit 14. The target score setting process is not limited to being executed at the time of "1. Goal setting" in FIG. 3, and may be executed at the time of "4. Schedule correction" in FIG. 3, for example. It may be executed by "1. Goal setting" after "5. Goal judgment" of 3.

Before the explanation of the target score setting process, the data input in STEP 53 of FIG. 6 will be supplemented.

In the series of processes of STEP 53 of FIG. 6, the skin support application 35a outputs the screen P1 shown in FIG. 19 to the display 31 as a part of the questionnaire. The screen P1 is a screen for inputting basic information for inferring whether the user Ua's subjective feeling or objective data is emphasized when thinking.

The screen P1 includes a bar P11, an icon P12, a subjective ratio display P13, a list P14 of questions about the idea, and an input completion button P15.

The characters "objective data" and "subjective sensation" are displayed at both ends of the bar P11. Further, the icon P12 is displayed on the bar P11. The icon P12 can be moved left and right by the operation of the user Ua.

Further, the subjective ratio display P13 is displayed in the information of the icon P12. The subjective ratio display P13 is a display in which the ratio of emphasizing the subjective sensation is represented by a number from 0 to 100, and the position of the icon P12 on the bar P11 becomes larger as it gets closer to the "subjective sensation", and the bar P11 The number on the subjective ratio display P13 changes so that the position of the upper icon P12 becomes smaller as it gets closer to the “objective data”.

The list of questions about the idea P14 includes a question and an input field for an answer. In the answer input field, either subjective selection indicating that "subjective sensation" is more important than "objective data" or objective selection indicating that "objective data" is more important than "subjective sensation". Is entered. For example, the answer "yes" to the question "I don't care if the health check value is bad but I don't feel it" indicates that "subjective feeling" is more important than "objective data". It is a subjective choice. On the other hand, the answer "No" to the question "I don't care if the value of the health diagnosis is bad but I don't feel it" indicates that "objective data" is more important than "subjective feeling". It is an objective choice.

When the skin support application 35a detects the pressing operation of the input completion button P15 via the touch panel 32, the input information is stored in the memory 36 and the screen P2 shown in FIG. 20 is output to the display 31.

The screen P2 is a screen for inputting basic information for determining the level of burden allowed by the user Ua, the target score of the skin condition of the user Ua, and the period for executing the measure.

The screen P2 includes a two-dimensional coordinate system having a load as a vertical axis and a period as a horizontal axis, and three arrows R1 to R3 extending from the origin to the first quadrant.

The arrow R1 indicates a course in which the skin condition of the user Ua is relatively greatly improved in a short period of time, although the burden is relatively heavy.

The arrow R3 indicates a course in which the burden is relatively small and the skin condition of the user Ua is relatively small and improved over a long period of time.

The load of the arrow R2 is smaller than the load of the arrow R1 and larger than the load of the arrow R3, the period of which is longer than the period of the arrow R1 and shorter than the period of the arrow R3, and the skin condition of the user Ua. It shows a course in which the degree of improvement is smaller than the arrow R1 and larger than the arrow R3.

When the skin support application 35a detects the pressing operation of any of the arrows R1 to R3 via the touch panel 32, the skin support application 35a recognizes the level of burden allowed by the user Ua corresponding to the selected arrow and the period for executing the measure. , Stored in the memory 36.

The skin support application 35a transmits the information stored in the memory 36 to the skin condition support server 10 in a series of processes of STEP 60.

The skin condition support server 10 executes the process of FIG. 21 in a state of receiving these information.

In STEP 71 of FIG. 21, the designated burden standard recognition unit 14 indicates a numerical value indicating a ratio that emphasizes the subjective sensation designated by the user Ua, which is input to the bar P11, the icon P12, and the subjective ratio display P13 of FIG. recognize. For example, in FIG. 19, 50 (%) is recognized as a ratio that emphasizes subjective sensations.

In STEP 72 of FIG. 21, the designated burden standard recognition unit 14 recognizes the number of subjective selections and the number of objective selections input to the list P14 of the question of FIG. For example, in the question rate of FIG. 19, "Yes" is a subjective selection that emphasizes subjective sensation rather than objective data, and "No" emphasizes "objective data" rather than "subjective sensation". It is an objective selection that shows. In FIG. 19, since there are four “yes” and one “no”, the designated burden standard recognition unit 14 recognizes that there are four subjective selections and one objective selection.

In STEP 73 of FIG. 21, the designated burden standard recognition unit 14 recognizes the ratio of emphasizing the subjective sensation and the ratio of emphasizing the user's subjective sensation based on the number of subjective selections and objective selections.

For example, the designated burden standard recognition unit 14 may recognize that both subjective and objective are equally emphasized from the ratio of emphasizing the subjective sensation recognized in STEP 71 of FIG. ..

Further, the designated burden standard recognition unit 14 calculates the ratio between the number of subjective selections and the number of objective selections from the number of subjective selections and objective selections recognized in STEP 72 of FIG. 21, and gives the user a subjective feeling. You may recognize the ratio of importance. For example, in the designated burden standard recognition unit 14, if there are four subjective selections and one objective selection, the user Ua places more importance on the subjective sensation than the objective data (subjective sensation). The ratio of emphasizing is 80%).

Further, the designated burden standard recognition unit 14 may recognize the ratio of emphasizing the subjective feeling of the user from these averages. For example, the designated burden standard recognition unit 14 attaches importance to the subjective sensation recognized in STEP 71 of FIG. 21 at 50%, and is subjective from the number of subjective selections and objective selections recognized in STEP 72 of FIG. 21. In STEP 74 of FIG. 21, when it is recognized that the ratio of emphasizing the subjective sensation is 80%, 65% of these average values may be recognized as the ratio of emphasizing the subjective sensation of the user Ua. The designated burden standard recognition unit 14 stores in the support DB 20 the ratio of emphasizing the subjective feeling of the user.

In STEP 75 of FIG. 21, the designated burden standard recognition unit 14 recognizes the level of the burden allowed by the user Ua, the target score of the skin condition of the user Ua, and the period for executing the measure, and stores them in the support DB 20. Of these, regarding the target score of the skin condition of the user Ua, the designated burden standard recognition unit 14 is based on the level of the burden allowed by the user Ua, the effect of each measure, and the ratio of emphasizing the subjective feeling of the user. Then, the subjective target score of the skin condition of the user Ua and the objective target score are determined. The designated burden standard recognition unit 14 recognizes the total value of the subjective target score of the skin condition of the user Ua and the objective target score as the target score of the skin condition of the user Ua.

[K. Decision processing of measures of the first embodiment]
With reference to FIGS. 22 to 24, the process of determining the measures performed in the series of processes of STEP 12 of FIG. 4 will be described. The measure determination process is a process executed by the measure extraction unit 15.

In STEP 81 of FIG. 22, the measure extraction unit 15 recognizes one measure from the measures included in the measure group. Instead of this, the measure extraction unit 15 may recognize one measure from all the measures, and matches the information input by the user among all the measures or the measures included in the measure group. You may recognize one measure.

For example, assuming that the measure shown in FIG. 23 is a measure included in the measure group, the measure extraction unit 15 recognizes the "eating antioxidant fruit" of the ID "S1". The data shown in FIG. 23 is the data stored in the support DB 20. The data shown in FIG. 23 corresponds to the "measure information" of the present invention.

In STEP 82 of FIG. 22, the measure extraction unit 15 evaluates the burden of the one measure. For example, as shown in FIG. 23, the burden is divided into "time burden", "financial burden", "psychological burden", and "objective difficulty" for each measure. The measure extraction unit 15 recognizes the total value of each of these scores as the burden of one measure. For example, the measure extraction unit 15 recognizes that the burden of "eating antioxidant fruit" of ID "S1" is 5. When the coefficient of each score is determined by the questionnaire input by the user Ua or the attribute of the user Ua, the measure extraction unit 15 multiplies each score and each coefficient, and then the sum of each is used as one measure. It may be recognized as a burden of.

The "time burden" indicates the length of time required to execute one measure. "Financial burden" refers to the amount of money required to implement one measure. The "psychological burden" indicates the magnitude of the psychological resistance that the user Ua feels when implementing the measure. "Objective difficulty" indicates the technical difficulty of the measure. "Time burden", "financial burden", "objective difficulty", and "psychological burden" may be predetermined values, or may be determined by questionnaires from a large number of users including users Ua, Ub, and Uc. It may be determined based on the questionnaire input by the user Ua, or it may be determined based on the history of the past behavior of the user Ua. In each numerical value, the larger the numerical value, the heavier the burden, and the smaller the numerical value, the lighter the burden.

In STEP 83 of FIG. 22, the measure extraction unit 15 recognizes the ratio of emphasizing the subjective sensation of the user Ua based on the ratio of emphasizing the subjective sensation of the user Ua stored in the support DB 20. Instead of or in addition to this, the measure extraction unit 15 may recognize the ratio of emphasizing the subjective feeling of the user Ua from the attributes such as the age and the setting of the user Ua. The ratio of emphasizing the subjective feeling of the user Ua corresponds to the "ratio determined from the attributes or preferences of the user" of the present invention.

In STEP 84 of FIG. 22, the measure extraction unit 15 recognizes the high effect of the one measure.

When the ratio of emphasizing the subjective feeling of the user Ua is 50%, the measure extraction unit 15 has 50% of the numerical value of the objective effect of the one measure shown in FIG. 23 and the numerical value of the subjective effect. The total value of 50% is recognized as the effect of the one measure. In the following description, it is assumed that the ratio of emphasizing the subjective feeling of the user Ua is 50%.

When the ratio of emphasizing the subjective feeling of the user Ua is 80%, the measure extraction unit 15 has 20% of the numerical value of the objective effect of the one measure shown in FIG. 23 and the numerical value of the subjective effect. The total value of 80% is recognized as the effect of the one measure.

The objective effect and the subjective effect in FIG. 23 may be, for example, an objective effect and a subjective effect on other users Ub and Uc who have implemented the same measure.

The effect of the measure means a numerical value indicating how much the implementation of the measure contributes to the improvement of the skin condition. The larger the numerical value of the effect of the measure, the greater the degree to which the implementation of the measure contributes to the improvement of the skin condition, and the smaller the numerical value of the effect of the measure, the smaller the degree to which the implementation of the measure contributes to the improvement of the skin condition. For example, the larger the numerical value of the objective effect of the measure, the easier it is for the implementation of the measure to increase the objective score of the skin condition, and the larger the numerical value of the subjective effect of the measure, the more the subjective score of the skin condition for the implementation of the measure. Is likely to rise.

For example, the effects of measures (objective effect and subjective effect) are the score of the skin condition before the implementation of the measure (objective score and subjective score) and the score of the skin condition after the implementation of the measure (objective score and subjective score). It may be represented by the average value, the minimum value, the maximum value, the mode value, the latest value, the median value, or the like of the difference from the above.

In this case, the effect of the measure is not always positive, and may be zero or negative. In this case, the negative effect of the measure means that the skin condition is rather worsened by the implementation of the measure.

In addition, the effect of the measure (objective effect and subjective effect) is the average value, minimum value, maximum value, mode value, latest value or the score of the skin condition (objective score and subjective score) after the implementation of the measure. It may be expressed by a median value or the like.

In this case, the score of the skin condition before the execution of the measure and the score of the skin condition after the execution of the measure are preferably the scores of the user Ua's past skin condition, but in place of or in addition to this. It may be the score of the past skin condition of the user Ub, Uc, etc., it may be a value predetermined by the system designer, or it may be a value derived by using a predetermined calculation formula. May be good.

In STEP 85 of FIG. 22, the measure extraction unit 15 classifies the one measure from the total value of the burden of the one measure and the height of the effect. In addition, the measure extraction unit 15 implements a measure such as a measure in which the effect of the measure is less than or equal to a predetermined value (for example, zero or negative), and the skin condition of the user Ua is expected to hardly improve or worsen. You may exclude it.

However, the effect of the measures may change depending on the age, season, environment, etc. of the user Ua. That is, even if the skin condition of the user Ua happens to be deteriorated by the execution of the measures, the skin condition of the user Ua may be improved from the next time onward, so that all the measures may be recommended.

For example, as shown in FIG. 24, the measure extraction unit 15 has a plurality of regions Z on the two-dimensional coordinate system on the two-dimensional coordinate system having the effect of the measure as the vertical axis and the burden of the measure as the horizontal axis. It is divided into ₁ to Z9, and the one measure is classified according to which area the one measure is included in.

In FIG. 24, each measure is classified as follows. In the following, X ₁ = 6.5, X ₂ = 8.5, Y ₁ = 5.5, and Y ₂ = 2.5.

Z ₁ : Area where the burden is less than X ₁ and the effect is Y ₁ or more Z ₂ : Area where the burden is X ₁ or more and less than X ₂ and the effect is Y ₁ or more Z ₃ : The burden is X ₂ or more and Area where the effect is Y ₁ or more Z ₄ : Area where the burden is less than X ₁ and the effect is Y ₂ or more and less than Y _1. Z ₅ : The burden is X ₁ or more and less than X ₂ and the effect is Y ₂ or more and less than Y ₁ . Area Z ₆ : Area where the burden is X2 or _more and the effect is Y2 or _more and _{less than} Y1 Z ₇ : Area where the burden is _less than X1 and the effect is less than Y2 Z ₈ : The burden is X1 or _more and X Areas less than ₂ and less _than Y2 Z ₉ : Areas with a burden of X2 or _more and an effect less _than Y2.

For example, the measure extraction unit 15 has 6 × 50% + 2 × 50% of the effect of “eating antioxidant fruit” of ID “S1” from “the ratio of emphasizing the subjective feeling of user Ua is 50%”. Recognize as = 4. The burden of "eating antioxidant fruit" of ID "S1" is 5 as described above.

Therefore, the measure extraction unit 15 classifies "eating antioxidant fruit" of ID "S1" into "region Z ₄ in which the burden is less than X ₁ and the effect is Y ₂ or more and less than Y ₁ ".

In STEP 86 of FIG. 22, the measure extraction unit 15 determines whether or not the processes of STEP 81 to STEP 85 have been executed for all the measures included in the measure group.

If the determination result is negative (NO in STEP86 in FIG. 22), the measure extraction unit 15 returns to STEP81 in FIG. 22 and executes the processes of STEP81 to STEP85 for the unprocessed measures.

If the determination result is affirmative (YES in STEP 86 in FIG. 22), in STEP 87, the measure extraction unit 15 recognizes the burden level stored in the support DB.

In STEP 88 of FIG. 22, the measure extraction unit 15 gives priority to each measure based on the burden level, classification, and effect.

For example, when the burden level is the burden level (large) corresponding to the arrow R1 in FIG. 20, the measure extraction unit 15 gives priority to each measure so that the measure with higher effect is prioritized over the measure with less burden. Give a degree. Further, when the burden level is the burden level (middle) corresponding to the arrow R2 in FIG. 20, the measure extraction unit 15 sets each measure so that the highly effective measures are prioritized within the range where the burden does not become excessively large. Give priority. When the burden level is the burden level (small) corresponding to the arrow R3 in FIG. 20, the measure extraction unit 15 gives priority to each measure so that the measure with the smaller burden is prioritized. The burden level corresponding to the arrows R1 to R3 may indicate the total or the upper limit of the average of the burden values of the measures.

The load levels corresponding to the arrows R1 to R3 are stored in the support DB 20. The burden level corresponding to the arrows R1 to R3 corresponds to the "burden standard" of the present invention, and the burden level corresponding to the arrows R1 to R3 designated by the user Ua corresponds to the "designated burden standard" of the present invention. ..

More specifically, when the measure extraction unit 15 has a burden level (large) corresponding to the arrow R1 in FIG. 20, the measure included in the area Z ₁ → the measure included in the area Z ₂ → included in the area Z ₃ . Measures to be taken → Measures included in Area Z ₄ → Measures included in Area Z ₅ → Measures included in Area Z ₆ → Measures included in Area Z ₇ → Measures included in Area Z ₈ → Measures included in Area Z ₉ Priority is given in the order of. When a plurality of measures are included in one area, the measure extraction unit 15 assigns priorities in descending order of effect, and when the effects are the same, in ascending order of burden.

Further, when the measure extraction unit 15 has a burden level (middle) corresponding to the arrow R2 in FIG. 20, the measure included in the area Z ₁ → the measure included in the area Z ₂ → the measure included in the area Z ₄ → the area. Measures included in Z ₅ → Measures included in Area Z ₇ → Measures included in Area Z ₈ → Measures included in Area Z ₃ → Measures included in Area Z ₆ → Measures included in Area Z ₉ have priority in this order Give a degree. When a plurality of measures are included in one area, the measure extraction unit 15 assigns priorities in descending order of effect, and when the effects are the same, in ascending order of burden.

Further, when the burden level (small) corresponding to the arrow R3 in FIG. 20 is the measure extraction unit 15, the measure included in the area Z ₁ → the measure included in the area Z ₄ → the measure included in the area Z ₇ → the area. Measures included in Z ₂ → Measures included in Area Z ₅ → Measures included in Area Z ₇ → Measures included in Area Z ₃ → Measures included in Area Z ₆ → Measures included in Area Z ₉ have priority in this order Give a degree. When a plurality of measures are included in one area, the measure extraction unit 15 assigns priorities in descending order of effect, and when the effects are the same, in ascending order of burden.

Instead of this, the measure extraction unit 15 may select the measures in descending order of effectiveness when the burden level (large) corresponding to the arrow R1 in FIG. 20 is reached. Further, when the burden level (small) corresponds to the arrow R3 in FIG. 20, the measures may be selected in ascending order of burden.

In STEP 89 of FIG. 22, the measure extraction unit 15 selects a measure to be recommended based on the priority. For example, when the measure extraction unit 15 selects four measures and the burden level (large) corresponds to the arrow R1 in FIG. 20, the measure extraction unit 15 selects the measures S6, S8, S1, and S2. Further, the measure extraction unit 15 selects the measures S6, S1, S2, and S4 when four measures are selected and the burden level (middle) corresponding to the arrow R2 in FIG. 20 is reached. Further, the measure extraction unit 15 selects the measures S6, S1, S2, and S3 when four measures are selected and the burden level (small) corresponding to the arrow R3 in FIG. 20 is reached.

The measure extraction unit 15 is not limited to selecting four measures, but may select measures up to a number specified by the user received from the user terminal 30 via communication, or may select a predetermined number. You may select measures until you reach the point, you may select measures until the number is linked to the arrows R1 to R3, or you may select measures within the range where the total burden does not exceed the predetermined value. good. Further, the measure extraction unit 15 may select a measure within a range in which the total of all the selected measures of time burden, financial burden, psychological burden, and objective difficulty does not exceed a predetermined value.

The measure extraction unit 15 stores the selected measure in the support DB 20.

[K. Decision processing of measures of the second embodiment]
The determination process of the measure of the second embodiment will be described with reference to FIGS. 25 to 27.

In this embodiment, as shown in FIG. 26, the measures are the types of measures such as "eating antioxidant fruit" and "running", and "one kind of fruit (eating)" and "running 1 km once a week". ) ”And the processing when it is classified as the degree of implementation of measures will be explained.

STEP91 to STEP98 in FIG. 25 are the same processes as STEP81 to STEP88 in FIG. 22. Therefore, the explanations of STEP91 to STEP98 are omitted. As a result of these processes, as shown in FIG. 27, the measure IDs “I-1” to “I-3”, “J- ₁ ” to “J- ₃ ” are classified into the regions Z1 to Z9. The priority is given in the same manner as in the first embodiment.

In STEP 99 of FIG. 25, the measure extraction unit 15 selects up to one recommended measure for each measure type and stores it in the support DB 20.

For example, when the measure extraction unit 15 selects two measures and the burden level (large) corresponds to the arrow R1 in FIG. 20, the measure extraction unit 15 selects the measures I-2 and J-3. Further, the measure extraction unit 15 selects the measures I-2 and J-2 when two measures are selected and when the burden level corresponds to the arrow R2 in FIG. 20 (middle). Further, the measure extraction unit 15 selects the measures I-2 and J-2 when the four measures are selected and when the burden level (small) corresponding to the arrow R3 in FIG. 20 is selected.

[L. Decision processing of measures of the third embodiment]
The determination process of the measure of the third embodiment will be described with reference to FIGS. 28 to 29.

The process of determining the measures of the third embodiment is a process of selecting up to a predetermined number of measures in ascending order of burden, and in descending order of effect when the burden is the same. For the sake of simplicity, FIG. 29 shows only the psychological burden as a burden, but if the magnitude of the burden can be determined by the total value or the like, it may be represented by a plurality of types of burden. ..

In STEP 101 of FIG. 28, the measure extraction unit 15 recognizes the burden search value. Specifically, the measure extraction unit 15 recognizes the minimum psychological burden value "1" as the burden search value.

In STEP 102 of FIG. 28, the measure extraction unit 15 recognizes each measure and each effect of the same burden as the burden search value. Taking FIG. 29 as an example, the measure extraction unit 15 recognizes the IDs “S9” to “S12”, which are the measures of the same burden as the burden search value “1”, and their effects. For example, when the ratio of emphasizing the subjective feeling of the user Ua is 50%, the measure extraction unit 15 recognizes the ID “S9” and its effect 6 × 50% + 2 × 50% = “4”. Hereinafter, the recognized measure group is referred to as a measure candidate group.

In STEP 103 of FIG. 28, the measure extraction unit 15 recognizes the maximum effect among the effects of the measures included in the measure candidate group as the effect search value. Taking FIG. 29 as an example, the measure extraction unit 15 recognizes the maximum effect value “4” as the effect search value.

In STEP 104 of FIG. 28, the measure extraction unit 15 recognizes a measure having the same effect as the effect search value as a measure candidate. Taking FIG. 29 as an example, the measure extraction unit 15 recognizes the measures of the IDs “S9” and “S12” having the same effect as the effect search value “4” as measure candidates.

In STEP 106 of FIG. 28, the measure extraction unit 15 determines whether or not the total number of measure candidates is equal to or greater than the upper limit of the number of measures according to the burden level.

The measure extraction unit 15 recognizes a relatively large value (for example, 5) as the upper limit of the number of measures when the burden level (large) corresponding to the arrow R1 in FIG. 20 is large. When the burden level (small) corresponding to the arrow R3 in FIG. 20 is set, the measure extraction unit 15 recognizes a relatively small value (for example, one) as the upper limit of the number of measures. When the burden level (middle) corresponding to the arrow R2 in FIG. 20, the measure extraction unit 15 is smaller than the upper limit of the number of measures of the arrow R1 and larger than the upper limit of the number of measures of the arrow R3 (the upper limit of the number of measures of the arrow R3). For example, 3) is recognized as the upper limit of the number of measures.

The measure extraction unit 15 determines whether or not the total number of measure candidates is equal to or greater than the upper limit of the number of measures recognized as described above.

If the determination result is affirmative (YES in STEP 106 of FIG. 28), the measure extraction unit 15 proceeds to STEP 107 of FIG. 28 and stores the recognized measure candidate in the support DB 20. When the total number of measure candidates exceeds the upper limit of the number of measures, the measure extraction unit 15 narrows down the number of measures to be within the upper limit based on the preference of the user Ua or the attribute of the user Ua. Alternatively, the user terminal 30 may later display that the total number of measure candidates exceeds the upper limit of the number of measures, and ask the user Ua to select a measure.

If the determination result is negative (NO in STEP 106 of FIG. 28), the measure extraction unit 15 proceeds to STEP 108 of FIG. 28 and determines whether or not the measure candidate group has an unrecognized measure in STEP 104.

If the determination result is affirmative (YES in STEP 108 of FIG. 28), the measure extraction unit 15 proceeds to STEP 109 of FIG. 28, decreases the effect search value by 1, and then proceeds to STEP 104 of FIG. 28.

If the determination result is negative (NO in STEP 108 of FIG. 28), the measure extraction unit 15 proceeds to STEP 110 of FIG. 28, increments the burden search value by 1, and then proceeds to STEP 102 of FIG. 28.

[M. Decision processing of measures of the fourth embodiment]
The determination process of the measure of the fourth embodiment will be described with reference to FIGS. 30 to 31.

In this embodiment, as shown in FIG. 31, the measures are the types of measures such as "eating antioxidant fruit" and "running", and "one kind of fruit (eating)" and "running 1 km once a week". ) ”And the processing when it is classified as the degree of implementation of measures will be explained.

STEP111 to STEP114 of FIG. 30 are the same processes as the processes of STEP101 to STEP104 of FIG. 28, respectively. Therefore, the description of STEP111 to STEP114 is omitted.

In STEP 115 of FIG. 30, the measure extraction unit 15 excludes measures of the same type as the measure candidates recognized in STEP 114 of FIG. 30. Here, "excluding the measure" means that the measure is not recognized as a measure candidate in STEP114 of the subsequent measure decision processing.

For example, when the measure ID “K-3” is recognized in FIG. 31, the measure IDs “K-1” and “K-2” of the same type are excluded. As a result, since only one measure of the same type with less burden and higher effect is selected, it is avoided that the measure of the same type is selected as a plurality of measure candidates.

STEP 115 to STEP 120 of FIG. 30 are the same processes as the processes of STEP 105 to STEP 110 of FIG. 28, respectively. Therefore, the description of STEP115 to STEP120 is omitted.

[N. Score display processing]
The details of the score display process of STEP 64 of FIG. 7 will be described with reference to FIGS. 32 to 33. The score display process is executed by the skin support application 35a.

In STEP 121 of FIG. 32, the skin support application 35a has a predetermined period based on the initial user information data and the current user information data of the user Ua stored in the support DB 20 of the skin condition support server 10 recognized via communication. The objective score of the skin condition of the user Ua is recognized and stored in the memory 36. Here, the "predetermined period" is preferably a period to which the relationship between the skin condition and the degree of implementation of the measure is shown, for example, one week, ten days, and one month before the execution time. Or for 3 months.

In STEP 122 of FIG. 32, the skin support application 35a determines whether or not the objective score of the user Ua is updated. For example, the skin support application 35a determines whether or not there is an objective score of the user Ua newly recognized on the execution date of the score display process. The objective score corresponds to the "first skin score" of the present invention.

If the determination result is negative (NO in STEP 122 of FIG. 32), the skin support application 35a proceeds to STEP 123a of FIG. 32, and based on the previous objective score of the user Ua, from the time of recognizing the previous objective score. The objective score of the user Ua up to the present time is estimated and stored in the memory 36.

FIG. 33A is a transition of the objective score from the time of the previous recognition of the objective score to the current time d1 before the time of the next recognition of the objective score. For example, in the skin support application 35a, as shown by the alternate long and short dash line in FIG. 33A, the objective score of the user Ua from the time of recognition of the previous objective score to the present d1 is the same as the previous objective score e1 of the user Ua. Suppose. This is because it is difficult to estimate the user's future objective score, especially from the first time to the second time when the objective score is recognized. From the third time onward, it is also possible to use the estimated value based on the degree of improvement of the objective degree score up to the previous time. Instead of this, the skin support application 35a is based on the time-series transition of the objective score before the previous two times of the user Ua, the season, the measures implemented by the user Ua, etc., in addition to the previous objective score of the user Ua. Then, the objective score of the user Ua from the time of the previous recognition of the objective score to the present time may be estimated. The graphs of FIGS. 33A and 33B are graphs in which the skin score is on the vertical axis and the period is on the horizontal axis.

If the determination result is positive (YES in STEP 122 of FIG. 32), the skin support application 35a proceeds to STEP 123b of FIG. 32 and is based on the previous objective score of the user Ua and the latest objective score of the user Ua. , The objective score of the user Ua from the time of the previous recognition of the objective score to the present time is estimated and stored in the memory 36.

FIG. 33B is a transition of the objective score from the time of the previous recognition of the objective score to the time of the current recognition of the objective score d2. For example, in the skin support application 35a, as shown by the alternate long and short dash line in FIG. 33B, the objective score of the user Ua from the previous objective score recognition time point to the current objective score recognition time point d2 is linearly transitioned. I presume that it was done. For the linear slope, a linear function is calculated from the previous objective score (e1) and the current objective score (e2) and the slope is used, or an approximate straight line is created in consideration of the input subjective score value. Then, the method of using the inclination can be considered.

After STEP123a of FIG. 32 or STEP123b of FIG. 32, the skin support application 35a proceeds to STEP124 of FIG. 32, and the initial user information of the user Ua stored in the support DB 20 of the skin condition support server 10 recognized via communication. Based on the data and the current user information data, the subjective score of the user Ua for a predetermined period is recognized and stored in the memory 36. The subjective score corresponds to the "second skin score" of the present invention.

In STEP 125 of FIG. 32, the skin support application 35a recognizes the score of the skin condition based on the objective score and the subjective score. Although not limited to this process, the skin support application 35a may evaluate the skin condition score based on the ratio of emphasizing the user's subjective sensation, similar to the recognition of the effect of STEP 84 in FIG. ..

In STEP 126 of FIG. 32, the skin support application 35a recognizes the target score of the skin condition of the user Ua stored in the support DB 20 of the skin condition support server 10 recognized via communication, and stores it in the memory 36.

In STEP 127 of FIG. 32, the skin support application 35a outputs a graph showing the transition of the recognized skin state score and the displays G1 and G2 showing the target score of the skin state to the display 31. When the estimation process of STEP123a of FIG. 32 is performed, for example, the solid line graph of FIG. 33A is output to the display 31. When the estimation process of STEP123b of FIG. 32 is performed, for example, the solid line graph of FIG. 33B is output to the display 31. The graph showing the transition of the skin condition score corresponds to the "display showing the transition of the skin condition in time series" of the present invention. The displays G1 and G2 indicating the target score of the skin condition correspond to the "display indicating the target score of the skin condition" of the present invention.

(Other embodiments)
In the present embodiment, an example in which the skin support application 35a processes the skin state as the "designated state" has been described, but the present invention is not limited to this, and the skin support application 35a processes the mental state or the physical state as the "designated state". You may go.

The user terminal 30 may execute a part or all of the processing of the skin condition support server 10. Further, the skin condition support server 10 may execute some or all of the processing other than the output and input of the user terminal 30.

The present invention is also realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiment is supplied to the system or device via a network or various storage media, and the computer (or CPU, MPU, etc.) of the system or device reads the program. This is the process to be executed.

1 ... Communication network, 10 ... Skin condition support server, 11 ... Skin condition recognition unit, 12 ... Measure group selection unit, 13 ... Measure information transmission unit, 19 ... Secondary data generation unit, 20 ... Support DB (database), 30 (30a, 30b, 30c) ... user terminal (smartphone), 31 ... display, 32 ... touch panel, 33 ... camera, 34 ... microphone, 35 ... CPU, 35a ... skin support application, 36 ... memory, 40 ... connection terminal, 45 ... Measuring equipment.

The information output system of the first invention is
An input unit that detects user input and
An output section that outputs information and
A designated burden standard recognition unit that recognizes a designated burden standard that is a burden standard designated via the input unit as information indicating the magnitude of the burden on the user due to the implementation of measures that the user can tolerate .
Measure extraction unit that extracts measures within the range of the burden indicated in the designated burden standard based on multiple measures for improving the skin condition, mental condition or physical condition and the burden of each of the multiple measures. When,
It is provided with an output control unit that outputs a display indicating the extracted measures to the output unit.
The burden standard is the upper limit of the technical difficulty of the measure.
It is characterized by that.

The information output system of the second invention is
An input unit that detects user input and
An output section that outputs information and
A designated burden standard recognition unit that recognizes a designated burden standard that is a burden standard designated via the input unit as information indicating the magnitude of the burden on the user due to the implementation of measures that the user can tolerate.
Measure extraction unit that extracts measures within the range of the burden indicated in the designated burden standard based on multiple measures for improving the skin condition, mental condition or physical condition and the burden of each of the multiple measures. When,
It is provided with an output control unit that outputs a display indicating the extracted measures to the output unit.
The burden standard is an upper limit of the psychological burden on the user due to the implementation of the measure.
It is characterized by that.
According to the information output system having the above configuration, the measure extraction unit extracts measures within the range of the burden shown in the designated burden standard based on the plurality of measures and the burdens of the plurality of measures.

The designated burden standard is a burden standard that is designated by the designated burden standard recognition unit via the input unit and indicates the burden on the user by implementing the measures that the user can tolerate . It is the upper limit of the difficulty level, and in the second invention, it is the upper limit of the psychological burden on the user due to the implementation of the measure .

According to the information output system of the configuration, the upper limit of the burden on the user due to the implementation of the measure that the user can tolerate (the technical difficulty of the measure, the psychological burden on the user due to the implementation of the measure) is specified by the user. Above, the measures whose burden on the user due to the implementation of the measures is within the specified range are extracted. As a result, it is possible to prevent the extraction of measures that impose an unacceptable burden on the user, such as being too difficult for the user or being too psychologically burdensome for the user. can do.

The information output system of the third invention is
An input unit that detects user input and
An output section that outputs information and
A designated state recognition unit that recognizes a designated state that is the user's skin state, mental state, or body state,
A database that stores as time-series data indicating the time-series transition of the specified state of the recognized user, and
The designated burden standard, which is the burden standard designated via the input unit, is recognized as information indicating the magnitude of the burden on the user due to the implementation of the measures that the user can tolerate, and is also recognized by the designated state recognition unit. A designated burden standard recognition unit that recognizes a subjective or objective target score that is a target value of the designated state based on the designated state, and a designated burden standard recognition unit.
A measure extraction unit that extracts measures within the range of the burden shown in the designated burden standard based on a plurality of measures for improving the designated state and the burden of each of the plurality of measures.
An output control unit that outputs a display showing the extracted measures, a display showing the target score of the designated state, and a display showing the transition of the time series of the designated state based on the time series data to the output unit. It is characterized by having

According to the information output system having this configuration, the designated state recognition unit recognizes the designated state, which is the user's skin state, mental state, or body state, and stores it in the database as time-series data indicating the time-series transition of the designated state. Will be done.

Then, the designated burden standard recognition unit recognizes the designated burden standard, which is the burden standard designated via the input unit, as information indicating the magnitude of the burden on the user due to the implementation of the measures that the user can tolerate, and also designates it. A subjective or objective target score, which is a target value of the designated state, is recognized based on the designated state recognized by the state recognition unit.

In addition, the measure extraction unit extracts measures within the range of the burden shown in the designated burden standard based on a plurality of measures for improving the designated state and the burden of each of the plurality of measures.

The designated burden standard is a burden standard that can be tolerated by the user and is designated via the input unit as information indicating the magnitude of the burden on the user due to the implementation of the measure.

Therefore, if the measure is within the range of the burden shown in this designated burden standard, it is highly probable that the user can tolerate it.

Then , the output control unit outputs to the output unit a display showing the extracted measures, a display showing the target score in the designated state, and a display showing the transition of the time series in the designated state.

As a result, it is possible to inform the measure that is highly likely to be within the range of the burden that the user can tolerate. In addition, the user can be made to recognize the time-series transition of his / her designated state and the difference from the target score of the designated state based on the designated state recognized by the designated state recognition unit.

Claims (9)

An input unit that detects user input and
An output section that outputs information and
A designated burden standard recognition unit that recognizes a designated burden standard, which is one burden standard designated via the input unit, from among a plurality of burden standards indicating the magnitude of the burden required to implement the measures that the user can tolerate.
Recognizing the degree to which the user attaches great importance to the subjective feeling of the designated state based on the user's attributes or preferences.
It is obtained by evaluating the result of the subjective evaluation of the user for the change of the designated state due to the execution of the measure and the result of the objective evaluation for the change of the designated state due to the execution of the measure according to the degree. Recognizing the effect of this measure,
The designation is based on a plurality of measures for improving the designated state, which is a skin condition, a mental state, or a physical condition, the burden of each of the plurality of measures, and the effect of each of the recognized plurality of measures. The measure extraction department that extracts measures within the range of the burden shown in the burden standard,
An information output system including an output control unit that outputs a display indicating the extracted measures to the output unit. In the information output system according to claim 1,
The burden standard is a burden value indicating the magnitude of the user's burden on the implementation of the measure that the user can tolerate, a time burden value indicating the magnitude of the time required to implement the measure, and the technical difficulty of the measure. An information output system characterized by showing at least one upper limit value among a difficulty level value indicating the above value and a psychological burden value indicating the magnitude of the psychological burden on the user in implementing the measure. In the information output system according to claim 1 or 2.
A designated state recognition unit that recognizes the user's designated state, and
A database that stores as time-series data indicating the time-series transition of the specified state of the recognized user is provided.
The designated burden standard recognition unit recognizes a subjective or objective target score which is a target value of the designated state based on the designated state recognized by the designated state recognition unit.
The output control unit outputs information to the output unit, a display showing a target score in the designated state and a display showing a time-series transition in the designated state based on the time-series data. system. In the information output system according to claim 3,
The designated burden standard recognition unit includes the degree to which the user recognized based on the attributes or preferences of the user attaches importance to the subjective feeling regarding the designated state, and the designated state recognized by the designated state recognition unit. , The subjective target score and the objective target score of the designated state are recognized, and the total value of the subjective target score and the objective target score is recognized as the target score of the designated state. An information output system characterized by In the information output system according to any one of claims 1 to 4,
The designated state of the user is an objective numerical value indicating a change in the designated state, a first score recognized at a predetermined time interval, and a subjective evaluation of the change in the designated state of the user. Information indicating that the first score is recognized separately at a time interval shorter than the recognition time interval, the second score is recognized, and the designated state recognition unit is provided. Output system. In the information output system according to claim 5,
A database is provided that stores the recognized first score and the second score as time-series data indicating the time-series transition of the designated state of the user.
The output control unit
Based on the first score and the second score recorded in the time series data, a display showing the transition of the time series in the designated state is configured to be output to the output unit.
When the output is performed, if the first score corresponding to the time when the second score is recognized is not included in the time series data, the first score included in the time series data is included. Or, when the estimated value of the first score at the time when the second score is recognized is recognized based on the second score, and the designated state is obtained based on the recognized estimated value and the second score. An information output system characterized by outputting a display indicating a series transition to the output unit. In the information output system according to claim 5 or 6.
The output control unit is an information output system characterized in that a display showing a time-series transition of the designated state is output to the output unit based on the total value of the first score and the second score. An input unit that detects user input and
In a system equipped with an output unit that outputs information,
A step of recognizing a designated burden standard, which is one burden standard designated via the input unit, from among a plurality of burden standards indicating the magnitude of the burden required to implement the measures that the user can tolerate.
A step of recognizing the degree to which the user attaches importance to the subjective feeling regarding the designated state based on the attribute or preference of the user.
It is obtained by evaluating the result of the subjective evaluation of the user for the change of the designated state due to the execution of the measure and the result of the objective evaluation for the change of the designated state due to the execution of the measure according to the degree. Steps to recognize the effect of the measure and
The designation is based on a plurality of measures for improving the designated state, which is a skin condition, a mental state, or a physical condition, the burden of each of the plurality of measures, and the effect of each of the recognized plurality of measures. Steps to extract measures within the range of burden shown in the burden standard, and
A step of outputting a display indicating the extracted measures to the output unit, and
An information output program characterized by executing. An input unit that detects user input and
It is a method executed by a system equipped with an output unit that outputs information.
A step of recognizing a designated burden standard, which is one burden standard designated via the input unit, from among a plurality of burden standards indicating the magnitude of the burden required to implement the measures that the user can tolerate.
A step of recognizing the degree to which the user attaches importance to the subjective feeling regarding the designated state based on the attribute or preference of the user.
It is obtained by evaluating the result of the subjective evaluation of the user for the change of the designated state due to the execution of the measure and the result of the objective evaluation for the change of the designated state due to the execution of the measure according to the degree. Steps to recognize the effect of the measure and
The designation is based on a plurality of measures for improving the designated state, which is a skin condition, a mental state, or a physical condition, the burden of each of the plurality of measures, and the effect of each of the recognized plurality of measures. Steps to extract measures within the range of burden shown in the burden standard, and
A step of outputting a display indicating the extracted measures to the output unit, and
An information output method characterized by including.

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