JP7300018B2 - Information output system, skin condition support program and skin condition support method - Google Patents

Description

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

Conventionally, various tools are known for the care of skin conditions.

For example, Patent Literature 1 describes a skin condition explanation section for explaining typical patterns of skin conditions as a counseling tool used by cosmetics salespeople for users, and a skin condition explanation part for explaining the skin conditions. describes a counseling tool provided with an explanation display part of a skin care method necessary for skin care.

The skin condition explanation part has a subheading of "a condition that tends to be dehydrated" as a typical pattern of skin conditions, and a subheading of the skin condition in question, "The barrier function that protects the skin from external stimuli is also likely to decrease, … is considered.”

The description display portion of the skin care method includes the headings "Somewhat insufficient W moisturizing" and "Insufficient W moisturizing + lotion mask/cream" as skin care methods for the relevant skin condition.

For example, when judging that the customer's skin condition is slightly lacking in moisture, the cosmetics salesperson recommends that the customer perform "double moisturizing" displayed in the explanation display part of the skin care method. By comparing the condition with the counseling tool, it is possible to immediately present the user with measures according to the skin pattern.

Japanese Patent No. 4299080

However, the technique disclosed in Patent Literature 1 only displays uniform advice for each skin condition. For this reason, when the burden of implementing measures included in this advice is large, the user feels that the advice is excessive, and when the burden of implementing the measures included in this advice is small, the user feels that the advice 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. intended to

The information output system of the first invention is
an input unit for detecting user input;
an output unit that outputs information;
a designated burden standard recognizing unit that recognizes a designated burden standard that is a burden standard that is designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy that is acceptable to the user;
A measure extracting unit that extracts measures within the range of the burden shown in the specified burden criteria, based on multiple measures for improving the skin condition, mental condition, or physical condition and the burden of each of the multiple measures. and,
an output control unit that outputs a display indicating the extracted measures to the output unit;
The designated burden standard is characterized by being an upper limit of technical difficulty of the measure.

The information output system of the second invention is
an input unit for detecting user input;
an output unit that outputs information;
a designated burden standard recognizing unit that recognizes a designated burden standard that is a burden standard that is designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy that is acceptable to the user;
A measure extracting unit that extracts measures within the range of the burden shown in the specified burden criteria, based on multiple measures for improving the skin condition, mental condition, or physical condition and the burden of each of the multiple measures. and,
an output control unit that outputs a display indicating the extracted measures to the output unit;
The specified burden standard is characterized by being an upper limit value of the psychological burden imposed on the user by the implementation of the policy.
According to the information output system having this configuration, the measure extraction unit extracts measures within the range of the burden shown in the designated burden standard based on the plurality of policies and the respective burdens of the plurality of policies.

The specified burden standard is a burden standard that indicates the burden imposed on the user by the implementation of the measure that the user can accept, which is specified by the designated burden standard recognition unit via the input unit , and is the technology of the measure in the first invention. In the second invention, it is the upper limit of the psychological burden imposed on the user by the implementation of the policy .

According to the information output system with this configuration, the user specifies the upper limit of the burden (technical difficulty of the policy, psychological burden on the user due to the implementation of the policy) imposed on the user by the implementation of the policy that the user can tolerate. Above, a measure is extracted in which the burden imposed on the user by the implementation of the measure is within the specified range. As a result, it is possible to suppress the extraction of measures that impose an unacceptable burden on the user, such as being too difficult for the user or placing too much of a psychological burden on the user. can do.

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 that are highly likely to be 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 an appropriate measure to the user while adjusting the burden for implementing the measure according to the user's wishes.

In addition, the information output system of the third invention is
an input unit for detecting user input;
an output unit that outputs information;
a designated state recognition unit that recognizes a designated state, which is the user's skin state, mental state, or body state;
a database for storing time-series data indicating a time-series transition of the designated state of the recognized user;
Recognizing a designated burden standard, which is a burden standard designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy, which is acceptable to the user, and recognized by the designated state recognition unit a designated burden criterion recognition unit that recognizes a subjective or objective target score, which is a target value of the designated state, based on the designated state;
a measure extracting unit that extracts measures within the range of the burden shown in the designated burden criteria based on the plurality of policies for improving the designated state and the respective burdens of the plurality of policies;
An output control unit that outputs to the output unit a display showing the extracted measure, a display showing the target score of the specified state, and a display showing the time-series transition of the specified state based on the time-series data. and

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

Then, the designated burden standard recognizing unit recognizes the designated burden standard, which is the burden standard designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy, which is acceptable to the user, and also recognizes the designated burden standard. 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.

Also, the measure extracting unit extracts measures within the range of the burden shown in the designated burden criteria based on the plurality of policies for improving the designated state and the burden of each of the plurality of policies.

The specified burden standard is a burden standard designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy, which the user can tolerate.

Therefore, it is highly probable that the user will be able to accept the measure if it is within the scope of the burden indicated by the designated burden standard.

Then, the output control unit outputs to the output unit a display indicating the extracted measure, a display indicating the target score of the specified state, and a display indicating the time-series transition of the specified state.

This makes it possible to inform the user of measures that are 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 difference from the target score of the designated state based on the designated state recognized by the designated state recognition unit, along with the time-series transition of his designated state.

In the information output system of the present invention,
The designated burden criterion recognition unit recognizes the degree to which the user attaches importance to subjective feelings regarding the designated state recognized based on the user's attributes or preferences, and the designated state recognized by the designated state recognition unit. Recognizing the subjective target score and the objective target score of the specified state based on , and recognizing the total value of the subjective target score and the objective target score as the target score of the specified state preferably.

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

Therefore, by determining the target value of the specified state in consideration of which of the user's subjective feeling or objective numerical value is more important, the target value is more in line with the user's intention.

According to the information output system with this configuration, the degree to which the user attaches importance to the subjective feeling regarding the designated state recognized by the designated burden criterion recognition unit based on the user's attributes or preferences, and the designated state recognition unit recognizes The subjective target score and the objective target score of the specified state are recognized based on the specified state and the total value of the subjective target score and the objective target score is the target score of the specified state Recognized.

Thereby, it is possible to present the target value to the user according to which of the subjective feeling or the objective numerical value the user attaches importance to.

In the information output system information output system of the present invention,
A first score, which is an objective numerical value indicating a change in the designated state of the user and is recognized at predetermined time intervals, and a subjective evaluation of the change in the designated state of the user. and a second score recognized at a shorter time interval than the time interval at which the first score is recognized.

In order to obtain data of a specified state, for example, stratum corneum cells of the user's skin may be collected and analyzed. . It can also have a negative effect on your skin.

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

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

As a result, it is possible to obtain the data of the specified state in a timely manner while suppressing the user's trouble, cost burden, and influence on the specified state.

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

If 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 of acquiring the second score does not exist (for example, the most recent first score For example, it was recognized one month ago.) is assumed.

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

Thereby, even if there is no corresponding first score when the second score is recognized, the user can be made to recognize the score of the approximate designated state.

Explanatory drawing of the utilization form of a skin condition support server. FIG. 2 is a configuration diagram of a skin condition support server and a user terminal; Explanatory drawing of a series of skin support processing by a skin condition support server. A first flow chart of processing in the skin condition support server. A second flowchart of processing in the skin condition support server. 4 is a first flowchart of processing in a user terminal; The second flowchart of processing in the user terminal. Explanatory drawing of the analysis processing of the initial data of the skin, the mind, and the body based on the subjective data and the objective data. Explanatory drawing of digitization of a body state. Explanatory drawing of digitization of the state of mind. FIG. 11A is a diagram showing the relationship between each measure and its improvement trend, etc., FIG. 11B is a diagram showing the schedule of each process, and FIG. illustration. Explanatory diagram of a progress table based on daily monitoring during the period of image display. Explanatory drawing of the influence on the skin condition by a special case. FIG. 10 is an explanatory diagram of a display screen of a skin condition improvement degree on a user terminal; 15A is an explanatory diagram of an evaluation method of measures, FIG. 15A shows evaluation criteria of measures, and FIG. 15B shows an example of evaluation of measures. 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 the evaluation example of a living and a special case. Explanatory drawing of the determination method of a goal achievement level. Explanatory drawing of secondary data. Questionnaire screen for estimating the ratio of emphasizing the user's subjective feeling. Burden level selection screen. 4 is a flowchart of target score setting processing. 4 is a flowchart of policy determination processing according to the first embodiment; Data showing the measures, the burden of the measures, and the effects of the measures in the first embodiment. Explanatory drawing of classification of each measure in 1st Embodiment. FIG. 11 is a flowchart of policy determination processing according to the second embodiment; FIG. Data showing the measures, the burden of the measures, and the effects of the measures in the second embodiment. Explanatory drawing of classification of each measure in 2nd Embodiment. FIG. 11 is a flowchart of policy determination processing according to the third embodiment; FIG. Data showing the measures, the burden of the measures, and the effects of the measures in the third embodiment. FIG. 12 is a flowchart of policy determination processing according to the fourth embodiment; FIG. Data showing the policy, the burden of the policy, and the effect of the policy in the fourth embodiment. 4 is a flowchart of score display processing; In the graphs displayed in the score display process, FIG. 33A is a graph when the objective score from the time of recognition 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 Based on the objective score of , the graph when estimating the objective score from the time of recognition of the previous objective score to the current time.

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

[A. Usage form of skin condition support server]
The configuration of the skin condition support server 10 and its positioning with respect to the system constituting the present invention will be described with reference to FIG. The skin condition support server 10 is configured by a computer system including a CPU, memory, various interface circuits, and the like. The skin condition support server 10 improves or maintains the skin condition of a plurality of users U (Ua, Ub, and Uc are exemplified in FIG. 1) by executing the image display program held in the memory by the CPU. (image display processing).

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

Communication terminals 50 (50a and 50b are exemplified in FIG. 1) of persons in charge T (Ta and Tb are exemplified in FIG. 1) are also connected to the communication network 1. FIG. The person in charge T sends data including information such as appropriate skin care methods in consideration of user U's skin characteristics, hobbies and tastes, lifestyle, etc. to the skin condition support server 10 and the user terminal 30 via the communication terminal 50. to provide advice on improving 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 are not necessarily one-to-one. The user terminal 30 of the user U may be provided with advice on improving the user U's skin condition. For example, a method of providing advice to one or a plurality of user terminals 30 of a user U by a plurality of persons in charge T via respective communication terminals 50 may be used.

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

[B. Configuration of skin condition support server and user terminal]
The configurations 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 the image display program held in the memory by the CPU, whereby the skin condition recognition unit 11, the measure group selection unit 12, the measure information transmission unit 13, the specified burden standard recognition unit 14, It functions as a policy extraction unit 15 and a secondary data generation unit 19 . Processing by these configurations will be described later. The skin condition support server 10 also includes a support DB (database) 20 that holds various data used for image display processing of the user U. FIG. This support DB 20 is developed, for example, on a RAM, and can be rewritten by updating subjective and objective data, which will be described later.

Next, the user terminal 30 of this 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 section" of the present invention. The touch panel 32 corresponds to the "input section" of the present invention. Instead of or in addition to this, by recognizing the designation of the user 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, the camera 33 or the microphone 34 can be used as the " It may function as an "input unit".

In the present embodiment, the user terminal 30 is, for example, a smart phone, and is equipped with a camera 33, a microphone 34, and the like. Alternatively, a specialized imaging device may be used. The CPU 35 executes a program of an image display application 35a (hereinafter referred to as a skin support application 35a) held in the memory 36 so that the user U can obtain support from the skin condition support server 10 via the skin support application 35a. be in a state of enjoyment. The CPU 35 executing the skin support application 35a corresponds to the "first information output control section" and the "second information output control section" of the present invention.

In addition, the user U separately has a keratin collecting tape 37 (37a, 37b, and 37c are illustrated in FIG. 1) for obtaining skin cells. The keratin collecting tape 37 may be provided to the user U in advance by the person in charge T, 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 users different from "user Ua" are referred to as "other users Ub and Uc". .

[C. Series of processing by 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 performs "1. goal setting", "2. schedule determination", "3. monitoring", "4. schedule correction", and [5. Goal Judgment] and “6. Secondary Data Generation” are executed according to the flowcharts shown in FIGS. Further, the user terminal 30 executes the processing according to the flowcharts shown in FIGS. 6 and 7 according to the processing by the skin condition support server 10 in each step. The processing of the skin condition support server 10 and the CPU 35 of the user terminal 30 in each process will be described below with reference to the flow charts shown in FIGS.

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 with the skin support application 35a.

When the skin condition support server 10 receives the registration application from the user Ua in STEP10 of FIG. Then, image display processing after STEP 11 is started.

[D. Goal setting process]
Goal setting” shown in FIG. 3 is executed by the skin condition recognition unit 11 and the measure group selection unit 12 . The measure group selection unit 12 prompts the user terminal 30 in STEP 11 of FIG. Send data.

In the user terminal 30 that has received this initial information request data, the skin support application 35a, in STEP 51 of FIG. is displayed on the display 31 to prompt the input of . In response, the user terminal 30 transmits initial user information data including the information input by the user Ua to the skin condition support server 10 .

The skin condition recognition unit 11 receives the initial user information data in STEP 11 of FIG. Based on this, a target score (goal) for the skin condition is set.

Here, the initial user information data includes subjective data and objective data regarding skin condition, body condition, and mental condition. Although detailed definitions will be described later, subjective data is an item determined subjectively by the user, and objective data is data based on inspection results, image analysis, and factual information. The subjective data of the skin condition is data indicating the satisfaction level of the user Ua with respect to the current skin condition, for example, in 10 stages. The objective data of the skin condition is skin image data of the user Ua. In addition to the objective skin condition data included in the initial user information data, the objective skin condition data may include analysis data of the stratum corneum cells of the user Ua collected by the horny material collecting tape 37 . Specifically, the analytical data of stratum corneum cells are, for example, data relating to water retention capacity and sebum suitability. 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 keratin sampling 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 water retention capacity, sebum suitability, and the like.

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

In addition, the skin support application 35a displays the usage of the keratin collecting tape 37 on the display 31 to the user Ua, and prompts the user Ua to use the keratin collecting tape 37 and mail it separately. The skin support application 35a may prompt the user Ua to use the keratin collecting tape 37 and capture a skin image, and the captured image may be transmitted to the skin condition support server 10 .

As shown in FIG. 8, the skin condition recognition unit 11 sets the initial values of the skin condition, for example, a subjective score of 3, a skin image score of 3, a water retention ability score of 2, and a sebum suitability score. 1, and the totaled value is used as the skin condition score. The score may be represented by a decimal number instead of a positive integer, or may be represented by a negative number. The sum of the skin image score, the water retention ability score, and the sebum suitability score is hereinafter referred to as an “objective score” as appropriate. The objective score may be a score (numerical value) of the skin condition determined based on objective data. It may be the sebum amount of the user's skin or a value determined based on these. The objective score may be the mean, maximum or minimum of the skin image score, the water retention capacity score and the sebum suitability score, or the like.

Recognition of the water retention capacity score and sebum suitability score by analysis of stratum corneum cells is referred to as the first recognition method. Alternatively or additionally, the first recognition method is at least one of a method of measuring the moisture 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 may periodically send a message to the user terminal 30 prompting the user to use the keratin collecting tape 37 or the like. prompts the user to take action.
In this case, "regularly" does not have to be strictly at regular time intervals, and may be at regular intervals as long as the skin condition is not affected. For example, when the first recognition method is performed every three months, if the first recognition method is performed on January 1st, not only April 1st, which is just three months later, but also March, for example, one week before The message may be sent to the user terminal 30 around the 24th, or may be sent to the user terminal 30 around April 8, one week later, for example. In addition, when providing a long-term service, for example, if you want to check detailed improvements, set the first recognition method every month, and check the effect of seasonal changes on the skin condition every three months. The timing of recognition can be changed, such as by setting the first recognition method.

Recognition of the subjective score based on the subjective data of the skin condition entered in the questionnaire and recognition of the skin image score based on the skin image data of the user Ua are each referred to as a second recognition method. The second recognition method may recognize the skin condition of the user Ua by either recognizing a subjective score based on the subjective data of the skin condition entered in the questionnaire or recognizing the skin image score based on the skin image data of the user Ua. , may include methods different from these. Also, 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 time-consuming, complicated, and expensive. Further, frequent use of the keratin collecting tape 37 may adversely affect the skin of the user Ua.

For example, the first recognition method is performed every three months and the second recognition method is performed every day. Further, when the timing of performing the first recognition method and the timing of performing the second recognition method overlap, it is preferable to perform them at the same timing if possible, because accurate data can be obtained. However, even if the second recognition method is not performed when the first recognition method is performed, the present invention can be implemented and the effect can be obtained.

Note that the subjective score may be a score determined based on subjective data.

The subjective data and objective data of body condition are separated as shown in FIG. Although detailed definitions will be described later, similar to the subjective data and objective data of the skin, the subjective data of the body condition is an item determined subjectively by the user Ua, and the objective data is data based on test results, image analysis, and factual information. is. The subjective data on the body condition is obtained by the user Ua inputting a questionnaire through the skin support application 35a. The objective data of the body condition is 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 is measured by the measuring device 45 connected to the connection terminal 40 of the user terminal 30. Measurement data such as user Ua's blood pressure, arrhythmia, urinary components, blood components, etc., and data such as the number of headaches, stiff shoulders, etc., and fatigue level determinations obtained by inputting questionnaires 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 and objective data of the state of mind are separated as shown in FIG. Although detailed definitions will be described later, similar to the subjective data and objective data of the skin, the subjective data of the state of mind is determined subjectively by the user Ua. data based on The subjective data is acquired by inputting a questionnaire in the skin support application 35a. The objective data is obtained by inputting questionnaires (the frequency of laughter per day, etc.) in the skin support application 35a, and by measuring with a measurement device (estimation of psychological state from pulse monitoring, etc.). In preparation for future development of services other than skin care, the initial user information data may include information on the occurrence of various mental disorders.

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

Based on the subjective data and objective data of the user Ua's skin condition, body condition, and mental condition recognized from the initial user information data in this way, the skin condition recognition unit 11 recognizes as indicated by the triangles on the right side of FIG. , the initial values of the three axes are set, which are represented by scores of 1 to 9 for skin conditions, 1 to 6 for body conditions, and 1 to 6 for mental conditions. Similar to the skin condition score, the subjective score and objective score of the physical condition or mental condition are calculated from the subjective data and objective data of the physical condition or mental condition, and based on these, the physical condition score and the mental condition score are calculated. may be treated as

Further, the policy group selection unit 12 acquires the "policy category, desire, frequency", "current policy", and "desired skin and score" included in the initial user information data. The "category, desire, and frequency of measures", "current measures", and "desired skin and score" are input by the user Ua using the skin support application 35a. In addition to these, the measure group selection unit 12 may acquire “desired body and score” and “desired mind and score”.

Here, in the “desired skin and score”, “desired skin” means improvement of dryness, improvement of stiffness, improvement of sensitive skin, improvement of acne, improvement of wrinkles, improvement of spots, improvement of wrinkles, improvement of sagging, improvement of dullness, and improvement of dark circles. , 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 the score selected by the user on a scale of 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 subjective skin condition “improvement of dryness” and objective criterion of skin condition “minimize difference between water retention capacity and sebum suitability”. ” is associated with.

For example, when the “desired skin” is “improved dryness” and the satisfaction score for the dryness of the current skin condition is 3, it is associated with “improved dryness” according to the selection of the user Ua. A satisfaction level of 5 with respect to the subjective skin condition “improved dryness” of the user Ua is set as a subjective target score.

In addition, the measure group selection unit 12 sets an objective skin condition improvement target associated with "improvement of dryness". For example, the measure group selection unit 12 selects the skin condition of the user Ua based on the criterion "minimize the difference between the water retention capacity and the sebum suitability" associated with "improvement of dryness" according to the selection of the user Ua. Of these, a sebum suitability 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 user Ua's selection will be described later.

In addition, regarding the category of policy, preference, and frequency, categories include dietary habits, activities at home, exercise, and how to use cosmetics. , "the number of times advice is received per day" or the like is selected as the frequency.

The “measure currently being taken” is a measure that the user Ua has already taken, and is represented by the content and frequency or degree of “soaking in the bathtub” or the like.

[E. Schedule decision process]
The process of “2. Determination of schedule” shown in FIG. The measure group selection unit 12 selects a measure group for achieving the 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 skin condition, the improvement tendency of the objective skin condition, and the suitable surrounding environment, which are associated with each improvement target described above. 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 location information detected by the GPS sensor or the like registered in advance and the date and time acquired from the clock function of the terminal. to predict.

For example, the policy group selection unit 12 selects the desired category as "activity at home, eating habits, exercise", the season when the humidity is expected to be 50% on average, such as the rainy season, and the subjective goal. If the score is 5 or more in satisfaction for "dryness" and the objective target score is 2 or more in sebum suitability, the subjective condition improvement tendency includes "dryness improvement", and the objective condition improvement tendency is "sebum eligible Select measures that include "enhancement of sexuality" and that the category is any of "home activities, eating habits, and exercise", and that the suitable surrounding environment does not contradict 50% humidity.

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 time-series change of the skin condition of the other users Ub and Uc, or the implemented measure and the skin condition of the user Ua. is stored in the support DB 20, it may be the improvement tendency of the subjective state and the improvement tendency of the objective state estimated based on the information.

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

In addition, for example, the support DB 20 stores information on the measure "soaking in the bathtub" implemented by each of the other users Ub and Uc, and subjective skin conditions of each of the other users Ub and Uc before and after implementing the measure. Suppose that "satisfaction with dry feeling" is stored as a time-series change.

At this time, for each of the other users Ub and Uc, the measure group selection unit 12 selects, for example, the subjective data of the skin condition (dry feeling) on the day before the bath and on the day of the bath for the measure “soak in the bathtub”. Calculate the amount of change in the degree of satisfaction for Then, the measure group selection unit 12 obtains the average value of the variation of the average variation of the degree of satisfaction with regard to dryness for each of the other users Ub and Uc. For example, when the average value of the amount of change in "satisfaction with dry feeling" is equal to or greater than a predetermined value, the measure group selection unit 12 sets the improvement tendency of the subjective state of the measure "soak in the bathtub" to "improved dry feeling". Recognize. The improvement tendency of the objective state can also be recognized in the same way as the improvement tendency of the subjective state.

Based on the age and skin condition of the user Ua, 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 and the same skin condition.

Further, when the implemented measures and the chronological changes in the skin condition of the user Ua are stored in the support DB, the measure group selection unit 12 estimates based on the information calculated in the same manner as described above. The improvement tendency of the subjective state and the improvement tendency of the objective state may be recognized.

In the first schedule determination process for user Ua, the measure group selection unit 12 recognizes the improvement tendency of the subjective condition and the improvement tendency of the objective condition from the subjective data and objective data of the skin conditions of the other users Ub and Uc. However, in the user Ua's second schedule determination process, the improvement tendency of the subjective condition and the improvement tendency of the objective condition 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 not only the skin condition but also the subjective state improvement tendency and the objective state improvement tendency for the mental state and the physical state. Measures may be selected in consideration of the improvement tendency of the objective state.

The measure group selection unit 12 may exclude measures having the same content and the same frequency or degree as the “current measures” from the measure group. This is because it is considered unnecessary to propose 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 multiple measures so as to include "soak in the bathtub", "vitamin C intake", "vegetable intake", and "walk 10,000 steps or more". .

The policy information transmission unit 13 evaluates the priority of the policy among the policy groups according to the user Ua's "policy category, desire, frequency" and input, and determines the initial policy according to the priority.

Evaluation of the priority of measures and decision processing of the initial measures according to the priorities will be described later.

FIG. 12 shows an example of a schedule in which "soak in a bathtub," "eat vegetables," and "walk 10,000 steps or more" are selected as initial measures. The policy information transmission unit 13 transmits schedule data indicating the details of the schedule thus determined to the user terminal 30 .

The policy 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, goal setting and schedule determination are performed at START, daily monitoring is performed, schedule is revised every week, a progress graph is created after one month, and goal determination and new goals are set in the third month. A series of events of setting up are planned. In addition to or instead of the user Ua's specification, the policy information transmitting unit 13 may use a predetermined plan for performing each process for a certain period of time.

When the user terminal 30 receives the schedule data from the skin condition support server 10 in STEP 52 of FIG. 6, the skin support application 35a displays the schedule execution table as shown in FIG. plan can be displayed to prompt the user Ua to implement each measure. In the execution table of the schedule in FIG. 12, the contents of each measure (“Soak in a hot tub”, “Eat vegetables”, “Walk 10,000 steps or more”) are displayed.

[F. Monitoring process]
The step “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 using the skin support application 35a, uses the user terminal 30 to check the daily skin, body, and mental conditions, the implementation status of the measures specified by the schedule, and the measures other than the measures specified by the schedule. The implementation status of Ua's voluntary action (action outside the policy) is entered. The implementation status of the measure includes information indicating whether or not "soaking in a bathtub", "eating vegetables", and "walking 10,000 steps or more" were implemented, as well as "30 minutes", "soaking in a bathtub", and "300g". It includes the degree of implementation of measures expressed in terms of time, amount, etc., such as "eating vegetables,""15,000steps," and "walking."

In STEP53 of FIG. 6, the skin support application 35a advances the process to STEP60 when the state of the skin, body, and mind is input by the user Ua. Current user information data including subjective data and objective data regarding the state of mind is transmitted to the skin condition support server 10, and the process proceeds to STEP54. It should be noted that the skin support application 35a directly advances the processing to STEP54 when the user Ua does not input the state of the skin, body, and mind in STEP53 of FIG. The data transmitted here does not include the data on the stratum corneum cells collected by the keratin collecting tape 37 .

Further, in STEP 54 of FIG. 6, 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, and outputs execution status data indicating the schedule execution status. The data is transmitted to the skin condition support server 10 and the process proceeds to STEP 55 in FIG. When the user Ua does not input the execution status of the schedule (execution status of each measure) in STEP54 of FIG. 6, the skin support application 35a directly proceeds to STEP55.

Furthermore, in STEP55 of FIG. 7, the skin support application 35a advances the process to STEP62 when the user Ua inputs the implementation status of the non-policy action, and performs non-policy action execution data indicating the details of the non-policy action that has been performed. is transmitted to the skin condition support server 10, and the process proceeds to STEP56. It should be noted that the skin support application 35a advances the processing to STEP56 as it is when the user Ua does not input the implementation status of the action outside the policy in STEP55 of FIG.

STEP 13 in FIG. 4 to STEP 16 in FIG. 5 and STEP 20 to STEP 22 in FIG. 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, accumulates the current user information data in the support DB 20, and 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 process proceeds to STEP 14 as it is.

Also, when the policy information transmitting unit 13 receives the execution status data from the user terminal 30 in STEP 14 , it advances the process to STEP 21 , accumulates the execution status data in the support DB 20 , and advances the process to STEP 15 . On the other hand, if it is determined in STEP14 that the execution status data has not been received from the user terminal 30, the process proceeds directly to STEP15.

Furthermore, when the policy information transmission unit 13 receives the non-policy action execution data from the user terminal 30 in STEP 15, it advances the process to STEP 22, accumulates the non-policy action execution data in the support DB 20, and proceeds to STEP 16 in FIG. proceed. On the other hand, when the policy information transmitting unit 13 does not receive the non-policy action execution data from the user terminal 30 in STEP15, the process proceeds to STEP16 in FIG. 5 as it is.

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

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

The schedule progress table also includes the degree of implementation of measures (“30 minutes” soaking in a hot tub, “300g” eating vegetables, “15,000 steps” walking).

In the user terminal 30, the skin support application 35a advances the process to STEP 63 when receiving the progress chart data transmitted from the skin condition support server 10 in STEP 56 of FIG. The skin support application 35 a uses the progress table data stored in the memory 36 to display the progress table shown in FIG. 12 on the display 31 of the user terminal 30 .

In addition to the progress table data, the skin support application 35a also uses the initial user information data, the current user information data, and the execution status data of the user Ua that are recognized through communication and stored in the support DB 20 of the skin condition support server 10. , information indicating transitions and changes in each state of the user Ua's skin, body, and mind is displayed on the display 31 of the user terminal 30 using the non-policy action execution data and the like.

For example, as shown in FIG. 13, the skin support application 35a can be used to determine the behavior of the user Ua other than the measures according to the schedule (change of face washing method, receiving a massage, etc.), and the physical condition of the user (physiology, lack of sleep, etc.). , the relationship of 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 monitors, on a month-by-month basis, the user Ua's skin condition including keratin condition, psychological condition, skin care satisfaction, and cosmetic usage evaluation values. A radar chart for comparison is displayed on the display 31 .

The user Ua visually recognizes these displays by the skin support application 35a and confirms changes in the conditions of his/her own skin, body, and mind, thereby grasping the degree of improvement in the skin as well as changes in the conditions of the body and mind. Therefore, the target skin condition goal can be achieved while improving the condition of the skin, body, and mind in a well-balanced manner.

After STEP 63, the skin support application 35a proceeds to STEP 64 and executes score display processing shown in FIG. Details of the score display process will be described later.

[G. schedule modification]
The process of "4. schedule modification" shown in FIG. 3 is executed by the measure information transmitting unit 13 for each period set by the user Ua on the skin support application 35a (every week in FIG. 11B). STEP 17 to STEP 20 and STEP 30 to STEP 33 in FIG.

In STEP 17, the policy information transmission unit 13 incorporates the user Ua's skin condition target achievement level and schedule into the user Ua's initial user information data, current user information data, execution status data, and the like accumulated in the support DB 20. Evaluate the degree of implementation of each measure and the effect of each measure.

The policy information transmission unit 13 extracts the correlation between the skin condition and the physical or mental condition using the policy evaluation criteria shown in FIG. continuation of the policy, exclusion from the policy group, cancellation of the policy, and change to another policy.

In the evaluation criteria of FIG. 15A, four items are used as judgment items: presence or absence of implementation, effect on skin, effect on body, and effect on mind. If there is, and there is no adverse effect on the body and mind, it will be evaluated as A and will be judged to be continued. Note that, in FIG. 15A, a measure whose implementation rate exceeds a predetermined implementation rate is indicated as "implemented", and a measure whose implementation rate is equal to or lower than the predetermined implementation rate is indicated as "non-implemented". The same applies to FIGS. 12 and 15B.

When the timing of the impact of the policy and the duration of the impact are determined for each policy, the policy information transmission unit 13 calculates the impact of each policy based on the timing of the impact of the policy and the duration of the impact of the policy. You can judge.

For example, if it is determined that the effect of the measure "soaking in the bathtub" on the skin, the body, and the mind will affect the next day and will continue for only one day, the measure information transmission unit 13 will: For example, it is determined that the effect of the measure "soak in the bathtub" on December 15th is reflected in each state on December 16th.

In addition, if the effect of the measure "vegetable intake" on the skin, the body, and the mind is set to occur after one week and continue for only three days, the measure information transmission unit 13 For example, it is determined that the influence of the policy of "vegetable intake" on December 15th is reflected in each state from December 22nd to December 24th.

On the other hand, a measure that has a good effect on the skin but has a bad effect on either the body or mind is given a B rating and is judged to be canceled or changed to another measure. In addition, since it is considered that a measure whose implementation rate is equal to or less than a predetermined implementation rate imposes a heavy burden on the user Ua, it is evaluated as C and canceled or another measure (for example, a measure that reduces the load on the user Ua or another measure is implemented). measures).

The measure information transmission unit 13 may evaluate whether each measure has a good or bad effect on the skin, body, and mind by implementing each measure for only one day, or for a certain period of time such as several days or weeks. Implementation of each measure may be evaluated to determine whether it has a positive or negative effect on the skin, body, or mind. When the evaluation is performed for a certain period of time, the measure information transmission unit 13, for example, gives a B rating when any state is adversely affected at a given rate, a C rating when the implementation rate is below a given rate, and otherwise. In the case of , it is good as A evaluation. Instead of this, the policy information transmitting unit 13 may, for example, give a B evaluation when the average value of satisfaction in any state during a certain period of time is below a predetermined value. In addition, if the satisfaction level of any state in one day is below a predetermined level, and the average value of the satisfaction level of any state over a certain period of time is below a predetermined level, it will be evaluated as C, and any of the evaluations for the day If the level of satisfaction in any state falls below a predetermined level, or if the average value of satisfaction levels in any one state over a certain period of time falls below a predetermined level, it will be evaluated as B, and the level of satisfaction in any state in a day will be a predetermined level. value, and the average value of satisfaction in any state in a certain period of time exceeds a predetermined value, such as A evaluation, such as a one-day evaluation and a certain period of time evaluation may be used in combination. .

Further, when the degree of improvement of the skin condition score shown in FIG. It may be excluded from the policy group. When the degree of improvement in the score of the physical condition or the mental state is equal to or less than a predetermined degree of improvement, the measure information transmitting unit 13 selects the measures in which the degree of improvement in the score of the physical state or the mental state is equal to or less than the predetermined degree of improvement in the measure group. can be excluded from

FIG. 15B shows an example in which the evaluation criteria shown in FIG. 15A are applied to measures (soaking in a bathtub, eating vegetables, walking 10,000 steps or more) in this embodiment. According to FIG. 15B, the measure information transmission unit 13 gives an A rating for “soak in the bathtub” and determines to continue with the next schedule, and gives a B rating for “vegetable intake” and excludes it from the measure group. Decide to cancel the schedule or change to another measure, and give a C grade for "walking more than 10,000 steps", exclude from the measure group, cancel the next schedule or change to another measure. have decided.

The policy information transmission unit 13 determines the influence of a plurality of policies for each combination of the policies. For example, if the combination of "soaking in a hot tub" and "eating vegetables" is rated B or C, the measure information transmitting unit 13 determines whether only the single measures of "soaking in a hot tub" or "eating vegetables" are considered. , or a combination of any of these measures and another measure may be changed.

The measure information transmission unit 13 performs such evaluation processing to determine whether schedule correction (mainly by changing the measure group to another measure) is necessary or not. to correct the schedule. Then, the user terminal 30 transmits schedule correction data, which is data of the corrected schedule, and ST
Proceed to EP19. On the other hand, when it is determined that the schedule need not be revised, the measure information transmitting section 13 advances the process from STEP 18 in FIG. 5 to STEP 19 in FIG. 5, and in this case the schedule is not revised.

Next, in STEP 19, the policy information transmission unit 13, based on the initial user information data, the current user information data, the data on the execution of the action outside the policy, etc., performs each non-policy action (included in the schedule) In addition to measures, actions performed by users) are evaluated.

The policy information transmitting unit 13 uses the evaluation criteria for the behavior outside the policy shown in FIG. 16A to determine whether the behavior outside the policy is recommended or not. In the evaluation criteria of FIG. 16A, influences on each state of skin, body, and mind are used as judgment items.

If "there is a positive effect on the skin, body, or mind, and there is no negative effect on any of them," the evaluation is D, and implementation is recommended. On the other hand, if it "has a negative effect on the skin, body or mind," an E rating is given and a ban is proposed. In addition, if "there is no effect on the skin, body, or mind," the evaluation is F, and implementation is not recommended.

FIG. 16B shows an example in which the evaluation criteria shown in FIG. 16A are applied to behaviors outside the policy (receiving a massage, ingesting a large amount of chocolate) in this embodiment. According to FIG. 16B, the measure information transmitting unit 13 determines that “get a massage” is evaluated as D and is recommended to be implemented in the next schedule. In addition, regarding "a large amount of chocolate intake", it is evaluated as E, and it is decided to propose a measure to stop it in the next schedule (for example, an alternative to ingesting Japanese sweets).

When the measure information transmitting unit 13 decides to recommend or prohibit the execution of the measures incorporated in the schedule, or to propose to cancel or change the measures outside the measures, the process advances from STEP 20 to STEP 31 . Then, when the recommendation is determined, the process proceeds from STEP31 to STEP33, the non-policy action recommendation data recommending the execution of the non-policy action is transmitted to the user terminal 30, and the process proceeds to STEP13 in FIG.

On the other hand, when the policy information transmitting unit 13 decides to propose the prohibition, the process advances from STEP 31 to STEP 32, and transmits to the user terminal 30 non-policy action prohibition data proposing prohibition of the non-policy action. The process proceeds to STEP13.

If there is no non-policy action to be recommended or prohibited, the policy information transmitting unit 13 advances the process from STEP 20 to STEP 13 in FIG. If the non-policy action proposed to be prohibited includes an alternative action, non-policy action prohibition data proposing a change to the alternative action may be transmitted to the user terminal 30 instead of the prohibition proposal.

In the user terminal 30, when the schedule correction data is received from the skin condition support server 10 in STEP57 of FIG. 7, the skin support application 35a proceeds to STEP65 and corrects the schedule based on the schedule correction data. The skin support application 35a then updates the schedule data held in the memory 36 and advances the process to STEP58.

In addition, when the skin support application 35a receives the non-policy action recommendation data or the non-policy action prohibition data from the skin condition support server 10 in STEP58 of FIG. The display 31 of the user terminal 30 displays a screen informing of the recommendation or prohibition of the action. 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 recommended non-policy behavior may be used as a new policy to modify the schedule.

[H. Goal Judgment Process]
The process of "5. Goal determination" shown in FIG. It is executed by the selection unit 12 and the policy information transmission unit 13 .

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

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

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

The skin condition recognition unit 11 recognizes the subjective value of skin dryness (subjective score) and the objective value of skin condition (skin image score) 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 skin condition support and after 3 months based on the subjective value of skin dryness and the objective value of skin condition, Determine goal achievement.

In the example of FIG. 17, the subjective score of dryness increased from 3 to 5 in 3 months, so it was determined to be achieved (○). , the water retention capacity was maintained at 2, and the sebum suitability increased from 1 to 2, so it was determined to be achieved (○). Since both the subjective value and the objective value have achieved the goal, it is determined that the goal has been achieved as a whole.

In order to set a new goal when the goal is achieved, the skin condition recognition unit 11 and the measure group selection unit 12 repeat the process of "1. Goal setting" shown in FIG. The skin condition recognizing unit 11 and the measure group selecting unit 12 may perform the step of "2. Determine schedule" when the goal is not achieved, or perform the step of "1. Goal setting" according to the user's desire or progress. The process may be performed again.

[I. Secondary data generation]
The step of “6. Secondary data generation” shown in FIG. 3 is executed by the secondary data generator 19 . The secondary data generation unit 19 generates various data transmitted from a plurality of users U, such as initial user information data, stratum corneum analysis data, current user information data, execution status data, non-measure action execution data (hereinafter referred to as user-specific data). data) are sequentially stored in the support DB 20 for each user.

Then, the secondary data generation unit 19 analyzes the individual user data accumulated in the support DB 20, and, for example, as shown in FIG. ), support improvement targets (dryness, stiffness, sensitivity, acne, wrinkled feeling, etc.), measures proposed by the schedule (soaking in a bathtub, eating vegetables, walking more than 10,000 steps, etc.), and skin by implementing measures, Secondary data is generated that associates changes in each state of the body and mind.

18, the secondary data generation unit 19 also generates secondary data that associates each user's characteristics with the effects of each user's skin, body, and mental state due to the implementation of the non-policy action, as in FIG. Generate.

The secondary data generated in this manner is effectively used when selecting effective measures for improving the skin condition while having a positive effect on the body and mind of users with similar characteristics. be able to. For example, in the process of "2. Determination of Schedule" in FIG. 3 described above, the measure group selection unit 12 can refer to the secondary data and select measures that match the characteristics of the user Ua.

In addition, in the process of "4. Schedule correction" in FIG. can be referred to and the schedule can be changed to include more effective measures or actions outside the measures.

In addition, the secondary data can be effectively used to support skin conditions, and can be used for marketing purposes targeting users with certain characteristics (for example, outdoor-oriented women in their 30s living in Tokyo). can also be used. As such, the secondary data may be provided to other systems such as 60 shown in FIG.

[J. Target Score Setting Process]
The target score setting process executed in the series of processes in STEP11 of FIG. 4 will be described with reference to FIGS. 19 to 21. FIG. The target score setting process is a process executed by the designated burden standard recognition unit 14 . Note that the target score setting process is not limited to being executed during "1. Goal setting" in FIG. It may be executed in "1. Goal setting" after "5. Goal determination" in 3.

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

In a series of processes of STEP 53 in FIG. 6, the skin support application 35a outputs a screen P1 shown in FIG. 19 to the display 31 as part of the questionnaire. The screen P1 is a screen for inputting basic information for estimating which of the user Ua's subjective feeling and objective data should be considered more important.

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

Characters such as "objective data" and "subjective sensation" are displayed at both ends of the bar P11. An 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, a 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 subjective sensation is represented by a number from 0 to 100, and the closer the position of the icon P12 on the bar P11 is to the "subjective sensation", the larger the bar P11. The number of the subjective ratio display P13 changes so that the closer the position of the upper icon P12 is to the "objective data", the smaller it becomes.

The list P14 of questions about the way of thinking includes questions and input fields for answers. In the answer entry field, either a subjective choice indicating that "subjective perception" is emphasized over "objective data" or an objective choice indicating that "objective data" is emphasized over "subjective perception". is entered. For example, in response to the question, "I don't care if my health check scores are bad, but I don't feel it," answering "yes" indicates that "subjective feelings" are more important than "objective data." It is a subjective choice. On the other hand, in response to the question ``I don't care if my health check scores are bad, but I don't feel it'', the answer ``No'' indicates that ``objective data'' is more important than ``subjective feelings''. 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.

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

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

An arrow R1 indicates a course that relatively greatly improves the skin condition of the user Ua in a short period of time, although the burden is relatively large.

An arrow R3 indicates a course that is relatively less burdensome and improves the skin condition of the user Ua by a relatively small amount over a long period of time.

Arrow R2 indicates that the burden is smaller than the burden of arrow R1 and larger than the burden of arrow R3, the period is longer than the period of arrow R1 and shorter than the period of arrow R3, and the skin condition of user Ua. A course whose degree of improvement is less than that of arrow R1 and greater than that of arrow R3 is shown.

When the skin support application 35a detects a pressing operation of any of the arrows R1 to R3 via the touch panel 32, it recognizes the level of burden permitted by the user Ua corresponding to the selected arrow and the period for executing the measure. , is 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 during the series of processing in STEP60.

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

In STEP71 of FIG. 21, the designated burden criterion recognition unit 14 recognizes the numerical value indicating the ratio of emphasizing the subjective feeling 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 the rate of emphasizing subjective sensation.

In STEP72 of FIG. 21, the designated burden criterion recognition unit 14 recognizes the number of subjective selections and the number of objective selections input to the question list P14 of FIG. For example, in the question rate of FIG. 19, "yes" is a subjective choice that emphasizes subjective feelings rather than objective data, and "no" is a subjective choice that emphasizes "objective data" rather than "subjective feelings". It is an objective selection that indicates In FIG. 19, there are four "yes" and one "no", so the designated burden criterion recognition unit 14 recognizes that there are four subjective selections and one objective selection.

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

For example, the designated burden criterion recognition unit 14 may recognize that the user attaches importance to both subjectivity and objectivity, based on the ratio of emphasizing the subjective feeling recognized in STEP 71 of FIG. 21 . .

Moreover, the designated burden criterion 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. You may recognize the weighted ratio. For example, if there are four subjective selections and one objective selection, the designated burden criterion recognition unit 14 places importance on the subjective feeling of the user Ua four times more than the objective data (subjective feeling). 80%).

Also, the designated burden standard recognition unit 14 may recognize the ratio of emphasizing the user's subjective feeling from these averages. For example, the designated burden criterion recognition unit 14 emphasizes the subjective feeling recognized in STEP 71 of FIG. If it is recognized that the percentage of emphasizing subjective sensation is 80%, 65% of these average values may be recognized as the percentage of user Ua emphasizing subjective sensation. In STEP74 of FIG. The designated burden standard recognizing unit 14 stores the ratio of emphasizing the user's subjective feeling in the support DB 20 .

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

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

In STEP81 of FIG. 22, the policy extraction unit 15 recognizes one policy among the policies included in the policy group. Alternatively, the policy extraction unit 15 may recognize one policy out of all the policies, or out of all the policies or policies included in a policy group, match the information input by the user. One measure may be recognized.

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

In STEP82 of FIG. 22, the policy extraction unit 15 evaluates the burden of the one policy. For example, as shown in FIG. 23, the burden is divided into "time burden", "monetary burden", "psychological burden", and "objective difficulty" for each policy and scored. The policy extraction unit 15 recognizes the sum of these scores as the burden of one policy. For example, the policy extraction unit 15 recognizes the load of 5 for the ID “S1” “eat antioxidant fruit”. When the coefficient of each score is determined by the questionnaire input by the user Ua or the attributes of the user Ua, the measure extraction unit 15 multiplies each score by each coefficient, and then sums the respective values to obtain one measure. may be recognized as the burden of

The term “time burden” indicates the amount of time required to implement one policy. "Financial burden" indicates the amount of money required to implement one measure. "Psychological burden" indicates the degree of psychological resistance that the user Ua feels when executing the policy. "Objective difficulty" indicates the technical difficulty of the measure. "Time Burden", "Monetary Burden", "Objective Difficulty", and "Psychological Burden" may be predetermined values, or may be determined based on questionnaires from a large number of users including users Ua, Ub, and Uc. may be determined based on a questionnaire input by the user Ua, or may be determined based on the history of past actions of the user Ua. For both numerical values, 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 policy extraction unit 15 recognizes the ratio of emphasizing the subjective feeling of the user Ua based on the ratio of emphasizing the subjective feeling of the user Ua stored in the support DB 20 . Instead of or in addition to this, the policy extraction unit 15 may recognize the ratio of emphasizing the subjective feeling of the user Ua from attributes such as the age and category 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 STEP84 of FIG. 22, the policy extraction unit 15 recognizes the effect of the one policy.

If the rate of emphasizing the subjective feeling of the user Ua is 50%, the policy extraction unit 15 extracts 50% of the numerical value of the objective effect of the one policy shown in FIG. The value obtained by adding 50% is recognized as the effect of the one measure. In the following explanation, it is assumed that the ratio of emphasizing the user Ua's subjective feeling is 50%.

If the ratio of emphasizing the subjective feeling of the user Ua is 80%, the policy extraction unit 15 extracts 20% of the numerical value of the objective effect of the one policy shown in FIG. The value obtained by adding 80% is recognized as the effect of the one measure.

Note that the objective effect and subjective effect in FIG. 23 may be, for example, the objective effect and subjective effect for other users Ub and Uc who have implemented the same policy.

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 extent 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 extent to which the implementation of the measure contributes to the improvement of the skin condition. For example, the higher the numerical value of the objective effect of a measure, the more likely it is that the implementation of the measure will raise the objective score of skin condition, and the higher the numerical value of the subjective effect of the measure, the higher the subjective score of skin condition. tends to rise.

For example, the effect of a policy (objective effect and subjective effect) is obtained by comparing the skin condition score (objective score and subjective score) before the policy is implemented and the skin condition score (objective score and subjective score) after the policy is implemented. may be represented by an average value, minimum value, maximum value, mode value, latest value, median value, or the like, of differences from

In this case, the effect of the policy is not necessarily positive, and may be zero or negative. In this case, a negative effect of the measure means that the skin condition rather deteriorates due to 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 It may be represented by a median value or the like.

In this case, it is preferable that the score of the skin condition before execution of the measure and the score of the skin condition after the implementation of the measure are the past skin condition scores of the user Ua. It may be a score of the past skin condition of the user Ub, Uc, etc., a value predetermined by the system designer, or a value derived using a predetermined formula. good too.

In STEP85 of FIG. 22, the policy extraction unit 15 classifies the one policy based on the total burden value and effect level of the one policy. Note that the policy extraction unit 15 selects a policy that is expected to hardly improve or worsen the skin condition of the user Ua by executing the policy, such as a policy whose effect is less than or equal to a predetermined value (for example, zero or negative). may be excluded.

However, the effect of the policy may change depending on the user Ua's age, season, environment, and the like. That is, even if the skin condition of the user Ua happened to deteriorate in the past due to the execution of the measures, the skin condition of the user Ua may improve from the next time onward, so all measures may be recommended.

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

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

Z ₁ : area where burden is less than X ₁ and effect is Y ₁ or more Z ₂ : area where burden is X ₁ or more and less than X ₂ and effect is Y ₁ or more Z ₃ : burden is X ₂ or more and Area Z ₄ where the effect is Y ₁ or more and the effect 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 X ₂ or more and the effect is Y ₂ or more and less than Y ₁ Z ₇ : area where the burden is less than X ₁ and the effect is less than Y ₂ Z ₈ : burden is X ₁ or more X Area Z ₉ where the burden is less than ₂ and the effect is less than Y ₂ : the area where the burden is X ₂ or more and the effect is less than Y ₂ .

For example, the policy extraction unit 15 determines that the effect of ID "S1" "eat antioxidant fruit" is 6×50% + 2×50%, based on the fact that "50% of user Ua's subjective feelings are emphasized". = 4. The load of ID “S1” “eat antioxidant fruit” is 5 as described above.

Therefore, the policy extraction unit 15 classifies the ID "S1" of "eat antioxidant fruit" into the "region _Z4 where the burden is less than _X1 and the effect is _Y2 or more and less than _Y1 ".

In STEP86 of FIG. 22, the policy extraction unit 15 determines whether or not the processes of STEP81 to STEP85 have been executed for all the policies included in the policy group.

If the determination result is negative (NO in STEP86 in FIG. 22), the policy extraction unit 15 returns to STEP81 in FIG.

If the determination result is affirmative (YES in STEP86 of FIG. 22), in STEP87, the measure extraction unit 15 recognizes the burden level stored in the support DB.

In STEP88 of FIG. 22, the measure extraction unit 15 assigns a 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 arrow R1 in FIG. Give degrees. If the burden level is a burden level (medium) corresponding to arrow R2 in FIG. Give priority. When the burden level is the burden level (low) corresponding to the arrow R3 in FIG. 20, the measure extracting unit 15 gives priority to each measure so that the measure with the lightest burden is prioritized. The burden levels corresponding to the arrows R1 to R3 may indicate the total or average upper limit of the burden values of the measures.

Burden levels corresponding to arrows R1 to R3 are stored in the support DB20. The burden levels corresponding to the arrows R1 to R3 correspond to the "burden criteria" of the present invention, and the burden levels corresponding to the arrows R1 to R3 specified by the user Ua correspond to the "designated burden criteria" of the present invention. .

More specifically _, when the burden level (large) corresponding to arrow _R1 in FIG _. measures included in area _Z4 →measures included in area _Z5 →measures included in area _Z6 →measures included in area _Z7 →measures included in area _Z8 →measures included in area _Z9 Priority is given in the order of When a plurality of measures are included in one region, the measure extracting unit 15 gives priority in descending order of effect, and in descending order of burden when the effect is the same.

20, the measure extracting unit 15 extracts the measure included in the area _Z1 →the measure included in the area _Z2 →the measure included in the area _Z4 →the area Priority is given in the order of measures included in area _Z5 → measures included in area _Z7 → area _Z8 → measures included in area _Z3 → measures included in area _Z6 → measures included in areas _Z9 . Give degrees. When a plurality of measures are included in one region, the measure extracting unit 15 gives priority in descending order of effect, and in descending order of burden when the effect is the same.

20, the measure extracting unit 15 extracts measures included in area _Z1 →measures included in area _Z4 →measures included in area _Z7 →area Priority is given in the order of measures included in area _Z2 →measures included in area _Z5 →measures included in area _Z7 →measures included in area _Z3 →measures included in area _Z6 →measures included in area _Z9 . Give degrees. When a plurality of measures are included in one region, the measure extracting unit 15 gives priority in descending order of effect, and in descending order of burden when the effect is the same.

Alternatively, the measure extraction unit 15 may select measures in descending order of effectiveness when the burden level (large) corresponds to the arrow R1 in FIG. 20 . Also, if the burden level (small) corresponds to the arrow R3 in FIG. 20, the measures may be selected in order of decreasing burden.

In STEP89 of FIG. 22, the measure extraction unit 15 selects a measure to recommend based on the priority. For example, when selecting four measures and when the burden level (large) corresponds to the arrow R1 in FIG. 20, the measure extraction unit 15 selects measures S6, S8, S1, and S2. Further, when selecting four measures, and when the burden level (medium) corresponding to the arrow R2 in FIG. 20 is selected, the measure extraction unit 15 selects measures S6, S1, S2, and S4. Further, when selecting four measures and when the burden level (small) corresponds to arrow R3 in FIG. 20, the measure extraction unit 15 selects measures S6, S1, S2, and S3.

The measure extraction unit 15 is not limited to selecting four measures, and may select measures until the number specified by the user received from the user terminal 30 via communication is reached. measures may be selected until the number of measures is reached, measures may be selected until the number linked to the arrows R1 to R3 is reached, or measures may be selected within a range in which the total burden does not exceed a predetermined value. good. In addition, the measure extraction unit 15 may select measures within a range in which the sum of all selected measures of time burden, monetary burden, psychological burden, and objective difficulty does not exceed a predetermined value.

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

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

In this embodiment, as shown in FIG. 26, the measures include types of measures such as "eat antioxidant fruits" and "run", and "(eat one type of fruit)" and "run 1 km once a week. )”, etc., will be described.

STEP91 to STEP98 in FIG. 25 are similar to STEP81 to STEP88 in FIG. Therefore, the description of STEP91 to STEP98 is omitted. As a result of these processes, as shown in FIG. 27, policy IDs "I-1" to "I-3""J-1" to "J-3" are classified into areas Z ₁ to Z ₉ . 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 selecting two measures and when the burden level (large) corresponds to the arrow R1 in FIG. 20, the measure extraction unit 15 selects measures I-2 and J-3. If two measures are to be selected and the burden level (medium) corresponding to the arrow R2 in FIG. 20 is selected, the measure extraction unit 15 selects measures I-2 and J-2. Further, when selecting four measures and when the burden level (small) corresponds to the arrow R3 in FIG. 20, the measure extraction unit 15 selects measures I-2 and J-2.

[L. Decision processing of measures in the third embodiment]
The policy decision processing of the third embodiment will be described with reference to FIGS. 28 and 29. FIG.

The policy determination process of the third embodiment is a process of selecting up to a predetermined number of policies in descending order of burden, and in descending order of effect if the burden is the same. In order to simplify the explanation, FIG. 29 shows only the psychological burden as the burden, but if the magnitude of the burden can be determined by the total value or the like, it may be represented by multiple types of burden. .

In STEP 101 of FIG. 28, the policy extraction unit 15 recognizes the burden search value. Specifically, the policy 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. Using FIG. 29 as an example, the policy extraction unit 15 recognizes IDs “S9” to “S12”, which are policies with the same burden as the burden search value “1”, and their effects. For example, if the rate of emphasizing the subjective feeling of the user Ua is 50%, the policy extraction unit 15 recognizes the ID "S9" and its effect 6*50%+2*50%="4". Hereinafter, the recognized policy group will be referred to as a policy candidate group.

In STEP 103 of FIG. 28, the policy extraction unit 15 recognizes the maximum effect among the effects of the policies included in the policy candidate group as an effect search value. Using FIG. 29 as an example, the policy 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 measures having the same effect as the effect search value as measure candidates. Using FIG. 29 as an example, the measure extraction unit 15 recognizes measures with IDs “S9” and “S12” having the same effect as the effect search value “4” as candidate measures.

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

If the burden level (large) corresponds to the arrow R1 in FIG. 20, the policy extraction unit 15 recognizes a relatively large value (eg, 5) as the upper limit of the number of policies. If the burden level (small) corresponds to arrow R3 in FIG. 20, the policy extraction unit 15 recognizes a relatively small value (for example, 1) as the upper limit of the number of policies. If the burden level (medium) corresponding to the arrow R2 in FIG. 20, the policy extraction unit 15 determines a value ( For example, 3) is recognized as the upper limit of the number of policies.

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

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

If the determination result is negative (NO in STEP 106 in FIG. 28), the policy extraction unit 15 proceeds to STEP 108 in FIG.

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

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

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

In this embodiment, as shown in FIG. 31, the measures include types of measures such as "eat antioxidant fruit" and "run", and "(eat one type of fruit)" and "run 1 km once a week. )”, etc., will be described.

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

In STEP115 of FIG. 30, the policy extraction unit 15 excludes policies of the same type as the policy candidates recognized in STEP114 of FIG. Here, "exclude a policy" means that the policy is not recognized as a policy candidate in STEP 114 of the subsequent policy decision processing.

For example, when policy ID "K-3" is recognized in FIG. 31, policy IDs "K-1" and "K-2" of the same type are excluded. As a result, only one measure with a low burden and a high effect is selected from among the measures of the same type.

STEP115 to STEP120 in FIG. 30 are the same processing as STEP105 to STEP110 in FIG. 28, respectively. Therefore, the description of STEP115 to STEP120 is omitted.

[N. Score display processing]
Details of the score display processing in STEP64 of FIG. 7 will be described with reference to FIGS. The score display process is executed by the skin support application 35a.

In STEP 121 of FIG. 32, the skin support application 35a recognizes through communication, based on the initial user information data and the current user information data of the user Ua accumulated in the support DB 20 of the skin condition support server 10, for a predetermined period of time. 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 that indicates the relationship between the skin condition and the degree of implementation of the measure, for example, one week, ten days, or one month prior to the time of implementation. or 3 months.

In STEP 122 of FIG. 32, the skin support application 35a determines whether or not the objective score of the user Ua has been 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 this score display process. The objective score corresponds to the "first skin score" of the present invention.

If the determination result is negative (NO in STEP122 of FIG. 32), the skin support application 35a proceeds to STEP123a of FIG. The user Ua's objective score up to the present time is estimated and stored in the memory 36 .

FIG. 33A shows the transition of the objective score from the previous objective score recognition time to the current time d1 before the next objective score recognition time. For example, the skin support application 35a determines that the objective score of the user Ua from the time of recognition of the previous objective score to the present time d1 is the same as the previous objective score e1 of the user Ua, as indicated by the dashed line in FIG. 33A. Assume that This is because it is difficult to guess the user's future objective score, especially between the first and second times the objective score is known. From the third time onwards, it is also possible to use an estimated value based on the degree of improvement in the objectivity score up to the previous time. Alternatively, the skin support application 35a, in addition to the previous objective score of the user Ua, based on the time-series transition of the objective score of the user Ua before the time before last, the season, the measures taken by the user Ua, etc. , the objective score of the user Ua from the time when the previous objective score was recognized to the current time may be estimated. Note that the graphs of FIGS. 33A and 33B are graphs in which the vertical axis is the skin score and the horizontal axis is the period.

If the determination result is affirmative (YES in STEP122 of FIG. 32), the skin support application 35a proceeds to STEP123b of FIG. , the objective score of the user Ua from the previous recognition of the objective score to the current time is estimated and stored in the memory 36 .

FIG. 33B shows the transition of the objective score from the previous objective score recognition point to the current objective score recognition point d2. For example, in the skin support application 35a, as indicated by the dashed 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 transitions linearly. We assume that Regarding 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 considering the input subjective score value. It is possible to think of a method such as using the slope by

After STEP 123a in FIG. 32 or STEP 123b in FIG. 32, the skin support application 35a proceeds to STEP 124 in FIG. Based on the data and the current user information data, the user Ua's subjective score 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 skin condition score based on the objective score and the subjective score. Although not limited to this process, the skin support application 35a may evaluate the score of the skin condition based on the ratio of emphasizing the user's subjective feeling, similar to recognition of the effect in STEP84 of FIG. .

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

In STEP 127 of FIG. 32, the skin support application 35a causes the display 31 to output a graph showing the transition of the score of the recognized skin condition and displays G1 and G2 showing the target score of the skin condition. When the estimation process of STEP 123a in FIG. 32 is performed, the solid line graph in FIG. 33A is output to the display 31, for example. When the estimation process of STEP 123b in FIG. 32 is performed, the solid line graph in FIG. 33B is output to the display 31, for example. The graph showing the transition of the skin condition score corresponds to the "display showing the time-series transition of the skin condition" 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 performs processing with the skin condition as the "specified state" has been described, but the present invention is not limited to this. you can go

The user terminal 30 may perform part or all of the processing of the skin condition support server 10 . Also, the skin condition support server 10 may perform 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, the software (program) that realizes the functions of the above-described embodiments is supplied to a 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.

Reference Signs List 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.

Claims (6)

an input unit for detecting user input;
an output unit that outputs information;
a designated burden standard recognizing unit that recognizes a designated burden standard that is a burden standard that is designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy that is acceptable to the user;
A measure extracting unit that extracts measures within the range of the burden shown in the specified burden criteria, based on multiple measures for improving the skin condition, mental condition, or physical condition and the burden of each of the multiple measures. and,
an output control unit that outputs a display indicating the extracted measures to the output unit;
The information output system, wherein the designated burden standard is an upper limit of technical difficulty of the measure. an input unit for detecting user input;
an output unit that outputs information;
a designated burden standard recognizing unit that recognizes a designated burden standard that is a burden standard that is designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy that is acceptable to the user;
A measure extracting unit that extracts measures within the range of the burden shown in the specified burden criteria, based on a plurality of measures for improving the skin condition, mental condition, or physical condition and the burden of each of the plurality of measures. and,
an output control unit that outputs a display indicating the extracted measures to the output unit;
The information output system, wherein the designated burden standard is an upper limit of the psychological burden imposed on the user by the implementation of the measure. an input unit for detecting user input;
an output unit that outputs information;
a designated state recognition unit that recognizes a designated state, which is the user's skin state, mental state, or body state;
a database for storing time-series data indicating a time-series transition of the designated state of the recognized user;
Recognizing a designated burden standard, which is a burden standard designated via the input unit as information indicating the size of the burden imposed on the user by the implementation of the policy, which is acceptable to the user, and recognized by the designated state recognition unit a designated burden criterion recognition unit that recognizes a subjective or objective target score, which is a target value of the designated state, based on the designated state;
a measure extracting unit that extracts measures within the range of the burden shown in the designated burden criteria based on the plurality of policies for improving the designated state and the respective burdens of the plurality of policies;
An output control unit that outputs to the output unit a display showing the extracted measure, a display showing the target score of the specified state, and a display showing the time-series transition of the specified state based on the time-series data. An information output system characterized by comprising: In the information output system according to claim 3,
The designated burden criterion recognition unit recognizes the degree to which the user attaches importance to subjective feelings regarding the designated state recognized based on the user's attributes or preferences, and the designated state recognized by the designated state recognition unit. Recognizing the subjective target score and the objective target score of the specified state based on , and recognizing the total value of the subjective target score and the objective target score as the target score of the specified state An information output system characterized by: In the information output system according to claim 3 or 4,
A first score, which is an objective numerical value indicating a change in the designation state of the user and is recognized at predetermined time intervals, and a subjective evaluation of the change in the designation state of the user. and a second score recognized at a time interval shorter than the time interval at which the first score is recognized, and a specified state recognition unit that separately recognizes the information. output system. In the information output system according to claim 5,
a database that stores the recognized first score and second score as time-series data indicating a time-series transition of the designated state of the user;
The output control unit is
Based on the first score and the second score recorded in the time-series data, a display showing a time-series transition of the designated state is output to the output unit,
When the output is performed, if the first score corresponding to the time when the second score was recognized is not included in the time-series data, the first score included in the time-series data Or recognize the estimated value of the first score at the time when the second score is recognized based on the second score, and based on the recognized estimated value and the second score, at the time of the specified state An information output system, characterized by outputting a display showing a sequence transition to the output unit.

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