JP7280333B2 - image display device - Google Patents

Description

The present invention relates to an image display device .

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, with the technique disclosed in Patent Document 1, the user can grasp what kind of skin condition the proposed measures should be executed (time, amount, number of times per day, frequency of execution, etc.). It was difficult to let

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide an image display device that allows a user to recognize the relationship between the degree of execution of a measure and the skin condition.

The image display device of the first invention is
an image display unit that outputs information;
an input unit for detecting user input;
At least one of a user's level of execution of a group of measures, which is one or more measures, and the user's physical condition, mental condition, and physical condition when the group of measures is executed at the level of the value of the level of execution a score recognition unit that recognizes a score, which is information that quantifies one good or bad ;
a display indicating the degree of execution of the user's policy group recognized by the score recognition unit and a display indicating the score of at least one of the user's skin condition, mental condition, and physical condition; an output control unit for outputting to the display unit ;
a designation recognition unit that recognizes designation of a value of the degree of execution of the measure group by the user via the input unit;
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit calculates a predicted score, which is a predicted score of at least one of the user's skin condition, mental condition, and physical condition, when the measure group is executed at the specified degree of execution. The user recognized by analyzing information on the degree of execution of the group of measures by the user and information on at least one of the skin condition, mental condition, and physical condition, with the value of the degree of execution obtained as input. , is configured to recognize using information indicating the correlation between the degree of execution for each policy group and the good or bad of the prediction score,
The output control unit causes the image display unit to output a display showing the predicted score.
It is characterized by

Further, the image display device of the second invention is
an image display unit that outputs information;
an input unit for detecting user input;
At least one of a user's level of execution of a group of measures, which is one or more measures, and the user's physical condition, mental condition, and physical condition when the group of measures is executed at the level of the value of the level of execution a score recognition unit that recognizes a score, which is information that quantifies one good or bad;
a display indicating the degree of execution of the user's policy group recognized by the score recognition unit and a display indicating the score of at least one of the user's skin condition, mental condition, and physical condition; an output control unit for outputting to the display unit;
a designation recognition unit that recognizes designation of a value of the degree of execution of the measure group by the user via the input unit;
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit calculates a predicted score, which is a predicted score of at least one of the user's skin condition, mental condition, and physical condition, when the measure group is executed at the specified degree of execution. The value of the degree of execution is input, and the information of the degree of execution of the group of measures of a plurality of users and the information of at least one of the skin condition, mental condition, and physical condition are analyzed and recognized. It is configured to recognize using information indicating the correlation between the degree of execution of each policy group by a plurality of users and the quality of the prediction score,
The output control unit causes the image display unit to output a display showing the predicted score.
It is characterized by

According to the image display device having these configurations, the display indicating the degree of execution of the user's policy group recognized by the score recognition unit and at least one of the user's skin condition, mental condition, and physical condition A display showing the two scores is output to the image display section by the output control section.
Then, when the designation recognition unit recognizes the user's designation of the degree of execution of the measure group, the score recognition unit executes the measure group at the designated degree of execution, the user's skin condition, A predicted score, which is a predicted value of the score of at least one of the mental state and the body state, is recognized, and a display showing the predicted score is output to the image display unit by the output control unit.
This allows the user to intuitively understand the relationship between the degree of execution of the measure and the skin condition through the display of the predicted score of at least one of the user's skin condition, mental condition, and body condition when the degree of execution of the measure is changed. can be recognizable.

In addition, in the first invention, the prediction score of the user is recognized by analyzing information on the degree of execution of the group of measures by the user and information on at least one of skin condition, mental condition and physical condition. , is recognized using information indicating the correlation between the degree of execution for each measure group and the good or bad of the prediction score. It is possible to make the user recognize the predicted score that is in line with the actual state of the relationship.

In the second invention, the predicted score is recognized by analyzing information on the degree of execution of the group of measures by a plurality of users and information on at least one of skin condition, mental condition and physical condition. Since it is recognized using information indicating the correlation between the degree of execution of each policy group by the user and the quality of the prediction score, not only the user's own data but also the rich user's execution of the policy group It is possible to make the user recognize a predicted score that is in line with the reality of the relationship between the degree and the skin condition, mental condition, or body condition.

Further, in the image display device of the second invention,
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit recognizes the predicted score of at least one of the user's skin condition, mental condition, and physical condition when the measure group is executed at the specified degree of execution. and recognized by analyzing information on the degree of execution of the group of measures by the plurality of users, information indicating attributes, and information on at least one of skin condition, mental condition, and physical condition. , is configured to be recognized using information indicating the correlation of other users who have attributes similar to that of the user
is preferred.

The degree of execution of measures by users with similar attributes (e.g. age, gender, area of residence, preferences, skin characteristics, mental characteristics, physical characteristics, etc.) and the skin condition, mental condition, and physical condition of the user are highly likely to be similar to each other.
According to the image display device of this configuration, the predicted score is obtained by combining information on the degree of execution of a group of measures by a plurality of users, information indicating attributes, and information on at least one of skin condition, mental condition, and physical condition. Recognition is performed using information indicating the correlation between the degree of execution of each policy group by other users who have the same attribute as the user and the quality of the prediction score, which is recognized by analysis.
As a result, other users who have the same attributes as the user, that is, have a high probability that the relationship between the degree of execution of the measures and the user's skin condition, mental condition, and physical condition are similar, will be able to perform the group of measures. It is possible to make the user recognize a predicted score that is in line with the reality of the relationship between the degree and the skin condition, mental condition, or body condition.

In the image display device of the present invention,
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The output control unit is
changing the value of the degree of execution of the group of measures to be output to the image display unit to the value of the degree of execution of the group of measures recognized by the designation recognition unit;
The score value of at least one of the user's skin condition, mental condition, and body condition to be output to the image display unit is changed to the predicted score value recognized by the score recognition unit.
is preferred.

According to the image display device having this configuration, the value of the degree of execution of the group of measures output to the image display unit is changed to the specified value in accordance with the user's designation of the value of the degree of execution of the group of measures. At the same time, the score value of at least one of the skin condition, mental condition, and body condition output to the image display unit is changed to the predicted score value recognized by the score recognition unit.
This allows the user to better understand the relationship between the degree of execution of the measure and the skin condition through the display of the predicted score of at least one of the user's skin condition, mental condition, and physical condition when the degree of execution of the measure is changed. It can be recognized intuitively.

In the image display device of the present invention,
The score recognizing unit calculates, during a predetermined period, a value of the user's degree of execution of the measure group, and the skin condition, mental state, and body condition of the user when the measure group is executed at the value of the degree of execution. recognizing the score that quantifies the goodness or badness of at least one of the conditions;
The predetermined period of time is a predetermined period of time before the score recognition unit executes processing for recognizing the predicted score,
The output control unit displays the value of the degree of execution of the measure group by the user during the predetermined period recognized by the score recognition unit, and the skin condition, mental condition, and body condition of the user during the predetermined period. a display showing the score of at least one of
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit is configured to determine at least one of the predicted score of the user's skin condition, mental condition, and physical condition when the measure group is executed at the specified degree of execution for the same period as the predetermined period. is configured to recognize the specified execution degree value as an input and using the information indicating the correlation
is preferred.

According to the image display device having the above configuration, the score recognition unit receives as input the value of the degree of execution of the measure group by the user in the predetermined period, and the score when the measure group is executed at the degree of the value of the degree of execution. It is configured to recognize a score, which is information obtained by quantifying at least one of the user's skin condition, mental condition, and body condition. Note that the predetermined period is a predetermined period before the time when the score recognition unit executes processing for recognizing the predicted score.
In addition, when the designation recognition unit recognizes the designation of the value of the degree of execution of the measure group, the score recognition unit recognizes the user's performance when the measure group is executed with the specified degree of execution for the same period as the predetermined period. A predicted score of at least one of skin condition, mind condition and body condition is recognized.
That is, based on the degree of execution of measures during a predetermined period prior to the execution of processing for recognizing prediction scores, the degree of execution of a group of measures differs during the same period, rather than the prediction score at a certain future point in time. This allows the user to recognize the predicted score of how the user's skin condition, mental condition, and body condition should have changed.
This makes it possible for the user to realize that he or she should have put in a little more effort in implementing the measures, or that they should have relaxed a little more.

Explanatory drawing of the utilization form of a skin condition recognition system. FIG. 2 is a configuration diagram of a skin condition recognition system and a user terminal; Explanatory drawing of a series of skin support processing by a skin condition recognition system. The first flow chart of processing in the skin condition recognition system. A second flow chart of processing in the skin condition recognition system. 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. Flowchart of simulation processing. 20A is a diagram showing the user's skin condition score, mental condition score, and body condition score during a predetermined period; FIG. 20B is a diagram showing the implementation status of the user's measures during the predetermined period; FIG. 21A is a diagram showing the degree of execution of each policy by a user during a predetermined period; FIG. 21B is a diagram showing the degree of execution of each category by a user during a predetermined period; The figure which shows a simulation screen. The figure which shows the simulation screen when a category bar is pressed. A graph showing the relationship between the degree of implementation of measures and each score. The figure which shows an example of the simulation screen in other embodiment. The figure which shows another example of the simulation screen in other embodiment.

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 recognition system]
The configuration of the skin condition recognition system 10 and its positioning with respect to the system constituting the present invention will be described with reference to FIG. The skin condition recognition system 10 is configured by a computer system including a CPU, memory, various interface circuits, and the like. The skin condition recognition system 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 recognition system 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 user terminal 30 corresponds to the "image display device" 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 transmits 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 recognition system 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 do not necessarily have to be 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 recognition system 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 recognition system and user terminal]
The configurations of the skin condition recognition system 10 and the user terminal 30 will be described with reference to FIG. The skin condition recognition system 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, and the secondary data generation unit 19. function as Processing by these configurations will be described later. The skin condition recognition system 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 "image display 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".

It should be noted that the fact that one device "recognizes" information means that one device receives the information from another device, and that one device recognizes information stored in a storage medium connected to the one device. reading, obtaining information by a device based on a signal output from a sensor connected to the device, or obtaining information received by a device or information stored in a storage medium or from a sensor Derivation of the information by executing predetermined arithmetic processing (calculation processing, search processing, etc.) based on the information obtained, one device passing the information as a result of arithmetic processing by another device to the other device It means that any arithmetic processing for obtaining the information is performed, such as receiving from, or reading the information from an internal storage device or an external storage device according to the received signal.

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, thereby allowing the user U to receive support from the skin condition recognition system 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 "score recognition section", "output control section" and "designation recognition 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. A series of processing by the skin condition recognition system]
Next, a series of processes by the skin condition recognition system will be described with reference to FIG. The skin condition recognition system 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 recognition system 10 in each step. The processing of the skin condition recognition system 10 and the CPU 35 of the user terminal 30 in each step will be described below with reference to the flowcharts 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 recognition system 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 information input by the user Ua to the skin condition recognition system 10 . The skin condition recognition unit 11 receives the initial user information data in STEP 11 of FIG. Based on this, a target level (goal) for 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 recognition system 10, The skin condition recognition system 10 may analyze the image of the keratin collecting tape 37 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 recognition system 10 .

As shown in FIG. 8, the skin condition recognition unit 11 sets the initial value of the skin condition to a subjective score of 3, a skin image score of 3, a water retention ability score of 2, and a sebum suitability score of 1. , and the total 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.

Recognition of the water retention capacity score and sebum suitability score by analysis of stratum corneum cells is called 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. Also, when the timings for performing the first recognition method and the second recognition method overlap, it is preferable to perform them at the same timing, in order to obtain accurate data. 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 recognized 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, subjective data is an item determined subjectively by the user Ua, and objective data is data based on test results, image analysis, and factual information, similar to the subjective data and objective data of the skin. 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 includes 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 data of the user Ua measured by the measuring device 45 connected to the connection terminal 40 of the user terminal 30. They are measurement data such as blood pressure, arrhythmia, urinary components, blood components, etc., and data such as the number of headaches, stiff shoulders, and other poor physical conditions obtained by inputting questionnaires in the skin support application 35a, fatigue level determination, and the like. 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, subjective data is an item determined subjectively by the user Ua, and objective data is data based on test results, image analysis, and factual information, similar to the subjective data and objective data of the skin. . 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 measure group selection unit 12 acquires the "desired skin level", "category, desire and frequency of measures" and "current measures" included in the initial user information data. The "desired skin level", "category, desire and frequency of measures" and "current measures" are input by the user Ua through the skin support application 35a.

Here, in the "desired skin level", "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, improvement of dark circles, It is a skin condition improvement target selected from complexion improvement and firmness improvement. The “level” is the level of satisfaction of the user Ua with respect to each target skin condition, and is the level selected by the user from 1 to 10 in the skin support application.

The support DB 20 stores the improvement tendency of the subjective state and the improvement tendency of the objective state of the skin condition associated with each improvement target. For example, as shown in FIG. 11C , “improvement of dryness” includes 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 level of 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 level.

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 determines that the user Ua's skin condition is lower than the water retention ability based on the criterion "minimize the difference between the water retention ability and the sebum suitability" associated with the "improvement of dryness". A sebum suitability value of 2 is set as the objective target level.

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 level and objective target level) 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 level is 5 or more in the satisfaction level of "dryness" and the objective target level 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 implemented by each of the other users Ub and Uc, chronological changes in the subjective data of the skin condition of each of the other users Ub and Uc before and after implementation of the measures, and other data. One or both of chronological changes in objective skin condition data for each of users 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. It is assumed 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 amount of change in the degree of satisfaction with respect 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 group according to the user Ua's "policy category, desire, and frequency", and determines the initial policy according to the priority. 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 recognition system 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 measures includes information indicating whether or not each of the measures, "soak in the bathtub,""eatvegetables," and "walk more than 10,000 steps," has been implemented, as well as "30 minutes,""soak in the bathtub,""300 g and "eating vegetables", "15,000 steps", 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 recognition system 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 information is transmitted to the skin condition recognition system 10, and the process proceeds to STEP55 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 recognition system 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, the level of skin condition (here, dry skin), the level of physical condition, the level of mental condition, measures (soaking in a bathtub, vegetables). 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, when the skin support application 35a receives the progress chart data transmitted from the skin condition recognition system 10 in STEP56 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 recognizes initial user information data, current user information data, and execution status data of the user Ua, which are recognized through communication and accumulated in the support DB 20 of the skin condition recognition system 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 advances to STEP 64 and executes simulator display processing shown in FIG. The details of the simulator display processing 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 the process proceeds to STEP19. 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 recognition system 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 recognition system 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 a subjective value (subjective level) of skin dryness and an objective value of skin condition (skin image score) based on 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 value level 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. Simulator display processing]
Details of the simulator display processing (STEP 64 in FIG. 7) executed by the skin support application 35a will be described with reference to FIGS. 19 to 24. FIG.

In STEP 71 of FIG. 19 , 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 recognition system 10, "predetermined The average value of each score of the skin condition, mental condition and body condition during the “period” is recognized and stored in the memory 36 . Here, the "predetermined period" is preferably a period that indicates the relationship between the skin condition, mental condition, physical condition, and the degree of implementation of the measure. 10 days, 1 month or 3 months. In this embodiment, the execution time is assumed to be April 10, 2017, and 10 days from April 1, 2017, which is nine days before the execution time, to the execution time will be described as a "predetermined period".

For example, the skin support application 35a calculates the average skin condition score of the user Ua based on the skin condition score, the mental condition score, and the physical condition score of the user Ua in a predetermined period, as shown in FIG. 20A. , average mental state score, and average physical state score are recognized and stored in the memory 36 . Here, the average skin condition score is 8.2, the average mental condition score is 5.0, and the average body condition score is 2.2.

In STEP72 of FIG. 19, the skin support application 35a recognizes each measure based on the initial user information data, current user information data, and execution status data accumulated in the support DB 20 of the skin condition recognition system 10 recognized through communication. For each measure, the degree of execution for each category of measures is recognized and stored in the memory 36 . The "degree of execution of policy" is a numerical value indicating the degree of execution of a policy determined for each policy. Examples of the "degree of execution of a measure" include the time to execute the measure, the amount of material consumed by the measure, the distance to implement the measure, the number of times the measure is executed per day, the execution time per execution of the measure, Included are the amount per execution of the policy and the frequency of execution of the policy over a given period of time.

For example, the skin support application 35a recognizes the degree of execution of the measure “vegetable intake” of the category “diet” shown in FIG. The degree of execution such as "intake amount" may be actually obtained data (for example, vegetable intake data) itself, or may be an evaluation value of actually obtained data. . For example, this evaluation value may be a value that increases continuously or intermittently as the value shown in the data approaches a predetermined reference value (for example, the amount of vegetable intake of 350 g, etc.). It may be a value that increases continuously or intermittently as the value indicated in the data increases, or may increase continuously or intermittently as the value indicated in the data decreases.

As shown in FIG. 21A, the skin support application 35a recognizes the average value and the maximum value of the degree of execution in a predetermined period for each measure, and stores them in the memory 36. FIG. The maximum value in the predetermined period may be the maximum value among the values performed by the user Ua, the theoretical maximum value, or a predetermined value.

The skin support application 35a takes the ratio of the average value and the maximum value of the degree of execution of the measure for each category, calculates the average value, calculates the degree of execution for each category, and stores it in the memory 36. Remember.

For example, the skin support application 35a calculates the degree of execution of the category "diet" by the following formula (1) based on the average value and the maximum value of the degree of execution in a predetermined period for each measure shown in FIG. evaluate. In addition, in Formula (1), 3 digits after the decimal point are rounded off.

In STEP73 of FIG. 19, the skin support application 35a outputs the entire simulator screen P1 to the display 31 of the user terminal 30a, as shown in FIG.

An area P10 surrounded by a triangle is displayed in the center of the entire simulator screen P1.

Outside the region P10 and around each vertex of the triangle, a display P11 showing the skin condition score, a display P12 showing the mental condition score, and a display P13 showing the body condition score are displayed.

The area P10 corresponds to the "predetermined area" of the present invention.

Displays P11, P12, P13 indicating respective scores include numerical displays P111, P121, P131, score slide bars P112, P122, P132, and score icons P113, P123, P133.

The score slide bars P112, P122, P132 and the score icons P113, P123, P133 correspond to the "display indicating at least one score of the user's skin condition, mental condition and physical condition" of the present invention.

The score slide bars P112, P122, P132 correspond to the "second line segment display" of the present invention.

The score icons P113, P123, P133 correspond to the "second icon" of the present invention.

The numerical display P111, the score slide bar P112, and the score icon P113 correspond to the "display showing the user's skin condition score" of the present invention.

The numerical displays P121 and P131, the score slide bars P122 and P132, and the score icons P123 and P133 correspond to the "display indicating at least one score of the user's physical state and mental state" of the present invention.

Each of the numerical displays P111, P121, and P131 displays the average value of the corresponding scores recognized in STEP71 of FIG.

Score icons P113, P123, P133 are displayed on the respective score slide bars P112, P122, P132 at positions corresponding to the average values of the corresponding scores recognized in STEP71 of FIG. Further, each score slide bar P112, P122, P132 is a line segment extending in the horizontal direction (horizontal direction of the paper surface) of the display 31 of the user terminal 30a. The horizontal direction of the display 31 corresponds to the "second direction" of the present invention.

Inside the area P10, category "diet", "behavior", and "skin care" displays P14, P15, and P16 of measures are displayed. Inside the area P10, all category displays may be displayed, the category display of the category designated by the user may be displayed, or the category display of the policy category recommended to the user may be displayed. Category display of the category of measures determined to have a high impact on at least one of the user's skin condition, mental condition, and physical condition based on the initial user information data, the current user information data, and the execution status may be displayed by a predetermined number.

Category slide bars P141, P151, P161 and category icons P142, P152, P162 are included in each category "diet", "behavior", and "skin care" display P14, P15, P16.

Category icons P142, P152, and P162 are displayed on the category slide bars P141, P151, and P161 at positions corresponding to the degrees of execution of the corresponding categories recognized in STEP72 of FIG. Further, each category slide bar P141, P151, P161 is a line segment extending in the vertical direction (vertical direction on the paper surface) of the display 31 of the user terminal 30a. The vertical direction of the display 31 corresponds to the "first direction" of the present invention.

The category slide bars P141, P151, P161 and the category icons P142, P152, P162 correspond to the "display indicating the degree of execution of the user's measures" of the present invention. Each category slide bar P141, P151, P161 corresponds to the "first line segment display" of the present invention. Each category icon P142, P152, P162 corresponds to the "first icon" of the present invention.

In STEP74 of FIG. 19, the skin support application 35a determines whether or not a pressing operation of any category slide bar has been detected via the touch panel 32. This operation has been described on the assumption that, for example, one of the category slide bars P141, P151, and P161 in FIG. can be

If the determination result of STEP74 in FIG. 19 is negative (STEP74, NO in FIG. 19), the skin support application 35a executes the process of STEP74 in FIG. 19 again.

19 is affirmative (STEP 74 . . . YES in FIG. 19), the skin support application 35a proceeds to STEP 75 in FIG. 19, and as shown in FIG. Display P17, P18 and P19.

The measure displays P17, P18, and P19 are measures of the category (hereinafter referred to as designated category) corresponding to the pressed slide bar. FIG. 23 shows measure displays P17, P18, and P19 of measures "vegetable intake", "water intake", and "three meals properly" when the pressing operation of the "meals" category slide bar P14 is detected.

The measure displays P17, P18, and P19 may display all measures, may display all measures included in a designated category, or may display measures being executed by the user. , measures recommended to the user may be displayed, and based on the initial user information data, the current user information data, and the execution status, the effect on at least one of the user's skin condition, mental condition, and physical condition is high. A predetermined number of measure displays of the measures determined to be may be displayed. It may be displayed in an additional manner (for example, downward of the category displays P14, P15, P16).

Policy icons P172, P182, and P192 are displayed on the policy slide bars P171, P181, and P191 at positions corresponding to the degrees of execution of the corresponding policies recognized in STEP72 of FIG. Further, each policy slide bar P171, P181, P191 is a line segment extending in the vertical direction (vertical direction of the paper surface) of the display 31 of the user terminal 30a.

The policy slide bars P171, P181, P191 and the policy icons P172, P182, P192 correspond to the "display showing the degree of execution of the user's policy" of the present invention. Each action slide bar P171, P181, P191 corresponds to the "first line segment display" of the present invention. Each policy icon P172, P182, P192 corresponds to the "first icon" of the present invention.

In STEP 76 of FIG. 19 , the skin support application 35a determines whether or not a pressing operation on any of the policy slide bars has been detected via the touch panel 32 .

If the determination result is negative (NO in STEP76 of FIG. 19), the skin support application 35a executes STEP76 of FIG. 19 again.

If the determination result is affirmative (YES in STEP76 in FIG. 19), the skin support application 35a proceeds to STEP77 in FIG. 19 and recognizes the pressed position on the measure slide bar. The pressed position on the policy slide bar corresponds to "the position of the first icon designated by the user via the input unit" of the present invention. The degree of execution of the policy corresponding to the pressed position on the policy slide bar corresponds to the "degree of execution of the specified policy group" of the present invention. The policy corresponding to the pressed policy slide bar corresponds to the "policy group" of the present invention.

In STEP78 of FIG. 19, the skin support application 35a predicts each score for the execution degree of the measure corresponding to the pressing position.

Each score is represented by the following equations (2) to (4).

Here, P(x) is the skin condition score of the user Ua, Q(x) is the mental condition score of the user Ua, and R(x) is the physical condition score of the user Ua.

i (i=1, . . . , n) is a number for identifying each policy.

xi (i=1, . . . , n) is the degree of execution of each measure i by the user Ua. The entire xi (i=1, . . . , n) (a vector consisting of all xi (i=1, . . . , n)) is denoted as x.

fi(xi), gi(xi), hi(xi) (i=1, . . . , n) are the scores P(x ), Q(x), and R(x). Each of fi(xi), gi(xi), hi(xi) (i=1, . . . , n) corresponds to an example of the "first function" of the present invention.

The line graph in FIG. 24 shows the relationship between the degree of execution of each measure "vegetable intake" by the user Ua and the scores P(x), Q(x) and R(x) of the user Ua. It is a line graph. This line graph shows, for example, the average of scores P(x), Q(x), and R(x) of user Ua shown in FIG. can be created by taking

In addition, in FIG. 24, approximated curves of each line graph are also displayed.

fi(xi), gi(xi), and hi(xi) can be represented, for example, by user Ua's scores P(x), Q(x), and R(x) indicated by approximated curves for each degree of execution. .

For example, if the intake of vegetable intake is 200 g, fi(xi) will be approximately 10.0, gi(xi) will be approximately 7.0, and hi(xi) will be approximately 2.0.

fi(xi), gi(xi), and hi(xi) are average values of scores of user Ua when user Ua implements each measure. It is possible that the impact of the policies of

Therefore, the degree of influence of each measure is adjusted by coefficients pi, qi, and ri. The coefficients pi, qi, and ri are obtained, for example, by the ratio of the degree of execution of each policy to the degree of execution of each policy. For example, when the measure s is executed at the execution degree a, the measure t is executed at the execution degree b, and the measure u is executed at the execution degree c, and the skin condition score is improved by d, the following formula (5 ) to (7) represent coefficients ps, pt, and pu. In this embodiment, the improvement of the skin condition score by d means that the average value of the skin condition scores after the implementation of the measure increased by d from the average value of the skin condition scores before the implementation of the measure. do.

k, l, and m are respective scores when no measure is implemented.

The skin support application 35a recognizes the degree of execution xi of the measure corresponding to the position of the icon on the measure slide bar for each measure i, and calculates each score P(x) using the above formulas (2) to (4). , Q(x), R(x). As for the measures included in the category corresponding to the unpressed category bar or the measures corresponding to the unpressed measure slide bar, the skin support application 35a selects each corresponding measure recognized in STEP72 of FIG. The degree of execution is used as the degree of execution xi of the policy. Each predicted score P(x), Q(x), R(x) corresponds to the "first predicted score" of the present invention. Each predicted score P(x) corresponds to the "second predicted score" of the present invention. Each predicted score Q(x), R(x) corresponds to the "third predicted score" of the present invention.

In STEP79 of FIG. 19, the skin support application 35a moves the score slide bars P112, P122, P132 to positions corresponding to the predicted scores P(x), Q(x), R(x). , score icons P113, P123 and P133 are displayed on the display 31. FIG.

After STEP79 in FIG. 19 is completed, the skin support application 35a executes the processes from STEP74 in FIG. Alternatively, after STEP79 in FIG. 19 ends, the skin support application 35a may execute the processing from STEP76 in FIG. 19 onward.

Such processing allows the user to recognize the effect on each score when the degree of implementation of the measure is changed.
(Other embodiments)
In the present embodiment, formulas (2) to (7) are used to predict the score according to the degree of each execution, but these formulas and Not limited to parameters. In order to improve the accuracy of the simulator, a person skilled in the art may make appropriate modifications such as changing the formula, changing the parameter calculation method, adding, deleting, or changing parameters.

When the skin support application 35a detects that the category slide bar has been pressed, the skin support application 35a displays the measure slide bar of the measures included in the category corresponding to the category slide bar (STEP 74 and STEP 75 in FIG. 19). , the skin support application 35a may change the position of the icon on the category slide bar to predict each score. In this case, the degree of execution of each measure may be changed evenly or at a predetermined ratio so as to follow the change in the degree of execution of the category. At this time, the skin support application 35a predicts each score by the formulas (2) to (4) from the degree of execution of each measure after the change, and each icon is displayed at the position corresponding to each predicted score. It outputs to the display 31 so that it may be located. Note that the policies included in the category corresponding to the pressed category slide bar correspond to the "policy group" of the present invention.

In this case, when the skin support application 35a detects that the category slide bar is pressed via the touch panel 32 with each icon positioned at a position corresponding to each predicted score, the category slide bar A measure slide bar for measures included in the corresponding category may be displayed. At this time, it is preferable that the position of the icon on each policy slide bar is a position corresponding to the degree of execution of each policy after the change.

The skin support application 35a may display measure displays P20, P21, and P22 as shown in FIG. 25 from the beginning instead of displaying the category slide bar.

The skin support application 35a may include, for example, a simulation target score display P31, other score displays P32 to P33, and a lifestyle display P34, as shown in FIG. The lifestyle display P34 is, for example, a display showing an average value of the degree of execution of each category or a value obtained by multiplying the degree of execution of each category by a coefficient for each category and totaling them. The skin support application 35a changes the degree of execution of each measure according to the change of the icon on the lifestyle display P34, predicts the score of the simulation target by formulas (2) to (4), and displays the score of the simulation target. You may change the icon on P31. The living display P34 corresponds to the "display showing the degree of execution of the user's policy group" of the present invention, and the other score displays P32 and P33 correspond to the "display showing the fluctuating score" of the present invention, and the simulation target score. The display P31 corresponds to the "display showing the simulated score" of the present invention.

In this case, the skin support application 35a displays a graph similar to FIG. , the simulation target score may be predicted and the icon on the simulation target score display P31 may be varied. The changed simulation target score display P31 corresponds to the "display showing the simulated prediction score" of the present invention.

In the present embodiment, all of the user Ua's skin condition, mental condition, and physical condition are simulated. Alternatively, a simulation of one of skin condition, mind condition and body condition may be performed. Also, a simulation regarding another state of the user Ua may be performed.

In the present embodiment, the first to third functions representing the relationship between the degree of execution of past measures by the user Ua and the skin condition, mental condition, and body condition of the user Ua are recognized, but the present invention is not limited to this. , other users Ub, Uc, the first to third functions may be recognized. Data of users Ub and Uc having attributes similar to those of user Ua may also be used. The attributes of the user Ua include, for example, the user Ua's age, gender, area of residence, preferences, skin characteristics, mental characteristics, and body characteristics (genetic information, etc.).

In the present embodiment, the score slide bar, the category slide bar, and the policy slide bar extend in orthogonal directions, but the present invention is not limited to this, and may extend in non-parallel directions or in parallel directions. may be

In the present embodiment, the degree of execution of a measure is displayed using the category slide bar, the measure slide bar, the category icon, and the measure icon. Also, colors, figures, characters, etc. that change according to the degree of execution of the measures may be displayed.

Similarly, for the score of each state, a color, figure, character, or the like that changes according to the score of each state may be displayed.

In the present embodiment, the CPU 35 executes the skin support application 35a to execute the processing of the "score recognition unit", "output control unit", and "designation recognition unit" of the present invention. The skin condition support system may execute part of the processing of the "score recognition section", "output control section", and "designation recognition section" of the present invention by communicating with each other and transmitting and receiving necessary data.

In the present embodiment, the term "function" refers to a function of outputting information such as numerical values such as scalar values or vector values by performing certain operations on input of information such as numerical values such as scalar values or vector values. Say what you have. In this embodiment, the functions fi(xi), gi(xi), and hi(xi) are used for each policy i. Alternatively or additionally, the function f (i,j)(xi,xj), g(i,j)(xi,xj), h(i,j)(xi,xj) may be used. Also, in this embodiment, a function is used for each score of each state, but instead of this, a common function may be used for a plurality of scores. The function may also perform classification, for example by machine learning. Each function may input a numerical value different from the degree of execution xi of each measure i, such as a numerical value representing the physical condition or mood of the user Ua, in addition to the degree xi of execution of each measure i.

The skin support application 35a may recognize the score of each condition by referring to the table based on the input value.

The skin support application 35a may recognize the score of each condition by transmitting the input value to the skin condition recognition system 10 and receiving the score of each condition.

In the present embodiment, the skin support application 35a predicts the score according to the specified degree of execution of the measure or category. can be predicted. For example, the skin support application 35a may allow the user Ua to select one measure or category via the touch panel 32, and predict the degree of execution of the one measure according to the designated score. In addition, the skin support application 35a allows the user Ua to input the rate of change for each measure or category via the touch panel 32, and varies the degree of execution of each measure according to the input percentage according to the specification of the score. may predict the degree of execution of each policy. For example, the skin support application 35a may vary the sleep time and vegetable intake to achieve a specified score at a rate of 100 g increase in vegetable intake for every 1 hour decrease in sleep time.

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 recognition system 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 (5)

an image display unit that outputs information;
an input unit for detecting user input;
At least one of a user's level of execution of a group of measures, which is one or more measures, and the user's physical condition, mental condition, and physical condition when the group of measures is executed at the level of the value of the level of execution a score recognition unit that recognizes a score, which is information that quantifies one good or bad;
a display indicating the degree of execution of the user's policy group recognized by the score recognition unit and a display indicating the score of at least one of the user's skin condition, mental condition, and physical condition; an output control unit for outputting to the display unit;
a designation recognition unit that recognizes designation of a value of the degree of execution of the measure group by the user via the input unit;
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit calculates a predicted score, which is a predicted score of at least one of the user's skin condition, mental condition, and physical condition, when the measure group is executed at the specified degree of execution. The user recognized by analyzing information on the degree of execution of the group of measures by the user and information on at least one of the skin condition, mental condition, and physical condition, with the value of the degree of execution obtained as input. , is configured to recognize using information indicating the correlation between the degree of execution for each policy group and the good or bad of the prediction score,
The image display device, wherein the output control section causes the image display section to output a display showing the predicted score. an image display unit that outputs information;
an input unit for detecting user input;
At least one of a user's level of execution of a group of measures, which is one or more measures, and the user's physical condition, mental condition, and physical condition when the group of measures is executed at the level of the value of the level of execution a score recognition unit that recognizes a score, which is information that quantifies one good or bad;
a display indicating the degree of execution of the user's policy group recognized by the score recognition unit and a display indicating the score of at least one of the user's skin condition, mental condition, and physical condition; an output control unit for outputting to the display unit;
a designation recognition unit that recognizes designation of a value of the degree of execution of the measure group by the user via the input unit;
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit calculates a predicted score, which is a predicted score of at least one of the user's skin condition, mental condition, and physical condition, when the measure group is executed at the specified degree of execution. The value of the degree of execution is input, and the information of the degree of execution of the group of measures of a plurality of users and the information of at least one of the skin condition, mental condition, and physical condition are analyzed and recognized. It is configured to recognize using information indicating the correlation between the degree of execution of each policy group by a plurality of users and the quality of the prediction score,
The image display device, wherein the output control section causes the image display section to output a display showing the predicted score. In the image display device according to claim 2,
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit recognizes the predicted score of at least one of the user's skin condition, mental condition, and physical condition when the measure group is executed at the specified degree of execution. and recognized by analyzing information on the degree of execution of the group of measures by the plurality of users, information indicating attributes, and information on at least one of skin condition, mental condition, and physical condition. , an image display device configured to recognize by using information indicating the correlation of another user having attributes similar to that of the user. In the image display device according to any one of claims 1 to 3,
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The output control unit is
changing the value of the degree of execution of the group of measures to be output to the image display unit to the value of the degree of execution of the group of measures recognized by the designation recognition unit, and the user's skin condition to be output to the image display unit; The image display device is configured to change the value of the score of at least one of the state of mind and the state of body to the value of the predicted score recognized by the score recognition unit. In the image display device according to any one of claims 1 to 4,
The score recognizing unit calculates, during a predetermined period, a value of the user's degree of execution of the measure group, and the skin condition, mental state, and body condition of the user when the measure group is executed at the degree of execution value. recognizing the score that quantifies the goodness or badness of at least one of the conditions;
The predetermined period of time is a predetermined period of time before the score recognition unit executes processing for recognizing the predicted score,
The output control unit displays the value of the degree of execution of the measure group by the user during the predetermined period recognized by the score recognition unit, and the skin condition, mental condition, and body condition of the user during the predetermined period. a display showing the score of at least one of
When the designation recognition unit recognizes the designation of the degree of execution of the measure group,
The score recognition unit is configured to obtain the predicted score of at least one of the user's skin condition, mental condition, and physical condition when the measure group is executed at the specified degree of execution for the same period as the predetermined period. is recognized using the information indicating the correlation with the value of the specified degree of execution as an input.

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