JP2018108373A - Skin condition recognition system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a skin condition recognition system capable of collecting abundant information about a user's skin condition while saving excessive increase in a load on a user.SOLUTION: A skin condition recognition device 10 comprises a skin condition recognition part 11 which recognizes the skin condition of a user U by a first recognition method or/and a second recognition method. The skin condition recognition part 11 periodically executes the first recognition method and executes the second recognition method at intervals shorter than that of the first recognition method.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a skin condition recognition system that supports improvement, maintenance, and the like of a user's skin condition.

  Conventionally, a skin condition recognition system for recognizing a skin condition has been proposed (see, for example, Patent Document 1 and Patent Document 2).

  In Patent Document 1, in addition to the moisture content data measured by the moisture meter, the diagnosis of the skin condition of the user is performed by taking into account the inquiry data including information about the user's age, sex, or living environment. A system for improving diagnostic accuracy is disclosed.

  In addition, in Patent Document 2, in addition to the peeled state of the skin stratum corneum measured by a skin stratum corneum peeling tape, etc., the health condition of the customer such as a cold is added to the skin analysis elements to improve the accuracy of the skin analysis. A system is disclosed.

JP 2002-172093 A JP 2004-354207 A

  The conventional technique described in Patent Document 1 and the technique described in Patent Document 2 focus on how to improve the accuracy of measurement of the skin condition per time. For this reason, it was necessary to implement a highly accurate method such as obtaining skin cells with a moisture meter or a skin horny layer peeling tape.

  However, when using a specialized tool such as a skin layer peeling tape, the recognition accuracy is improved, but the user's skin condition is impaired, the measurement takes time, or the use or purchase of a specialized tool is not recommended. There is a possibility that the burden on the user may increase, such as taking such a cost or taking time and effort for the user to prepare the environment.

  If measurement with such specialized tools is frequently performed, the burden on the user may increase excessively. On the other hand, since the user's skin is likely to change in a relatively short period of time, if the number of measurements becomes rare, the amount of information relating to the user's skin state may be insufficient, and the user's skin state may not be sufficiently grasped. There is.

  The present invention has been made in view of such a background, and a skin condition recognition system capable of collecting information relating to a user's skin condition with relatively high accuracy and abundantly while suppressing an excessive increase in the burden on the user. The purpose is to provide.

The skin condition recognition device of the present invention is
A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin state recognizing unit periodically executes the first recognition method and executes the second recognition method at an interval shorter than an interval of execution of the first recognition method.

  According to the skin condition recognition device having the above configuration, the skin condition recognition unit periodically executes the first recognition method, and the first recognition method has a higher recognition accuracy of the user's skin condition than the second recognition method. Therefore, the user's skin condition is regularly recognized with relatively high accuracy.

  Therefore, the skin condition recognition unit is measured by the first recognition method by executing the second recognition method, which is relatively less accurate than the first recognition method, at an interval shorter than the execution interval of the first recognition method. The user's skin condition recognized by the second recognition method can be supplemented with highly accurate user's skin condition information.

    On the other hand, in general, methods with relatively high skin state recognition accuracy include, for example, peeling cells of a user's skin with tape, making a diagnosis at a specialty store, and using relatively expensive equipment. The user may be burdened with a physical burden, a time burden, or a financial burden.

  For this reason, frequently repeating information acquisition by recognition of the first recognition method places a heavy burden on the user, but by acquiring information by recognition by the second recognition method at intervals shorter than the execution interval of the first recognition method. It is possible to acquire abundant information with relatively high accuracy while reducing the burden on the user.

  The skin condition recognition unit of the skin condition recognition apparatus of the present invention periodically executes the first recognition method, and the number of executions of the second recognition method in a predetermined period is greater than the number of executions of the first recognition method. The second recognition method may be configured so as to increase.

  The skin condition recognition unit of the skin condition recognition apparatus of the present invention periodically executes the first recognition method and executes the second recognition method at a frequency higher than the execution frequency of the first recognition method. May be configured.

  The skin condition recognition unit of the skin condition recognition apparatus of the present invention periodically executes the first recognition method, and at a timing different from the first recognition method in addition to the execution timing of the first recognition method. You may be comprised so that the 2nd recognition method may be performed.

In the skin condition recognition device of the present invention,
The skin condition recognition unit executes the second recognition method on both the execution date of the first recognition method and the non-execution date of the first recognition method, and the first recognition method uses the first recognition method. Based on the data recognized on the execution date, the data recognized on the execution date of the first recognition method by the second recognition method, and the data recognized by the second recognition method on the non-execution date of the first recognition method. It is preferable to recognize the skin condition of the user on the non-execution day of the first recognition method.

  The relationship between the user's skin state recognized by the first recognition method on one day and the user's skin state recognized by the second recognition method has the same tendency on other days Inferred.

  According to the skin condition recognition device configured in view of this point, the second recognition method is executed on both the execution date of the first recognition method and the non-execution date of the first recognition method. The data recognized on the execution date of the first recognition method by the first recognition method, the data recognized on the execution date of the first recognition method by the second recognition method, and the non-execution date of the first recognition method It is preferable to recognize the skin condition of the user on the non-execution date of the first recognition method based on the data recognized by the second recognition method.

  That is, the first recognition method is periodically executed, but the second execution method is executed at a timing at which the first recognition method is executed and at a timing between execution of the first recognition method. Therefore, the number of executions in a predetermined period is larger in the second recognition method than in the first recognition method. Alternatively, the execution frequency in the predetermined period is higher in the second recognition method than in the first recognition method.

  Accordingly, the first recognition method is not executed by taking into consideration the data recognized on the execution date of the first recognition method by the first recognition method and the data recognized on the execution date of the first recognition method by the second recognition method. The user's skin condition in the day can be recognized. Thereby, abundant and highly accurate information can be acquired.

  In the skin condition recognition apparatus of the present invention, it is preferable that the first recognition method includes a method of analyzing data indicating a cell state on the surface of the user's skin acquired by a tape.

  In the skin condition recognition device having the above configuration, the first recognition method is a recognition method that involves peeling of cells on the surface of the user's skin because the cells on the surface of the user's skin are acquired using a tape. According to the system, the second recognition method is executed at an interval shorter than the execution interval of the first recognition method. As a result, in acquiring relatively high-precision and abundant information, the frequency of execution of the recognition method that involves the separation of cells on the surface of the user's skin during a predetermined period can be suppressed, thereby increasing the physical burden on the user. It can be avoided.

  In the skin condition recognition device of the present invention, it is preferable that the first recognition method includes a method of recognizing the user's skin condition based on data measured by a specialized tool.

  In the present invention, the specialized tool is a device whose accuracy of measurement of the user's skin condition is higher than a predetermined accuracy, for example, a device that is often used in specialized institutions such as stores and hospitals.

  According to the skin condition recognition apparatus having the configuration, the first recognition method is a method for recognizing the user's skin condition based on data measured by the specialized tool. According to the system, the second recognition method is executed at an interval shorter than the execution interval of the first recognition method. Thereby, in acquiring relatively high accuracy and abundant information, the frequency of use of the user's specialized tools during a predetermined period can be suppressed, so that it is possible to avoid an increase in the user's time load or financial burden. .

  In the skin condition recognition device of the present invention, the second recognition method is a method of recognizing a user's skin condition based on an answer to a questionnaire about evaluation of the user's skin condition input at the user terminal, and is imaged at the user terminal. Measurement using a method for recognizing the user's skin condition based on the image of the skin, a method for recognizing the user's skin condition based on information received from the wearable device worn by the user, and a simple tool that is less accurate than a specialized tool It is preferable to include at least one of methods for recognizing the user's skin condition based on the information obtained.

  In the present invention, the simple tool is a device whose accuracy of measurement of the user's skin condition is less than a predetermined accuracy, for example, a home device. The accuracy threshold for separating the specialized tool from the simple tool may be the same as the accuracy threshold used in the specialized institution, or based on the price of each device, the accuracy that exceeds the predetermined price The threshold value may be set. Further, the threshold value of the specialized tool and the simple tool may be determined depending on whether the design or production purpose of the tool is for the purpose of acquiring information related to the skin.

  According to the skin condition recognition apparatus having the above configuration, the second recognition method is a method that is relatively easy to execute, such as using a user terminal, using a wearable device, or using a simple tool. Can be avoided.

In the skin condition recognition device of the present invention,
The first recognition method preferably includes at least a method of analyzing a cell state on the surface of the user's skin acquired by the keratin collection tape.

  According to the skin state recognition apparatus having the above configuration, the first recognition method includes at least a method for analyzing the state of the cells on the surface of the user's skin acquired by the keratin sampling tape. The structure can be recognized accurately.

In the skin condition recognition device of the present invention,
A storage unit for storing a plurality of measures;
After the execution of the first recognition method, a combination of a plurality of measures according to the user's skin condition at the time of execution of the first recognition method recognized by the first recognition method among the plurality of measures. A measure group selection section for selecting a measure group;
Each time the second recognition method is executed once or a plurality of times, a measure corresponding to the latest skin condition of the user recognized by the second recognition method is selected from the measure group, and the selected measure is indicated. It is preferable to include a measure information transmitting unit that transmits measure information to the user terminal.

  According to the skin condition recognition device of the configuration, a measure that is a combination of a plurality of measures according to the user's skin state recognized by the measure group selection unit by the measure group selection unit after the execution of the first recognition method. A group is selected. Since the first recognition method is a highly accurate recognition method of the user's skin condition, the measures included in the selected measure group are appropriate measures in view of the user's skin condition at the time of execution of the first recognition method. The probability is high.

  Moreover, the measure according to the latest skin condition of the user recognized by the second recognition method is selected from the measure group by the measure information transmission unit for each execution of the second recognition method once or a plurality of times. The selected measure information is transmitted to the user terminal. By outputting this measure information to the user terminal, the user can be made to recognize the measure according to the latest skin condition of the user.

Here, since the change in the user's skin condition takes time, the measures included in the measure group that has a high probability of being appropriate in view of the user's skin condition at the time of initial execution are also applied to the latest user's skin condition. There is a high probability of being appropriate.

  For this reason, even if the recognition accuracy of the second recognition method is lower than the recognition accuracy of the first recognition method, the measure information transmission unit has a high probability of being appropriate for the latest user skin condition. Measures are selected from Thereby, it is avoided that a measure with a high probability of being inappropriate for the user's skin condition is selected.

In the skin condition recognition device of the configuration,
The storage unit stores measures executed by the user and time-series transitions of the user's skin state,
The measure group selection unit includes a user's skin condition at the time of execution recognized by the first recognition method, a measure executed by the user, and the user after the second and subsequent executions of the first recognition method. It is preferable to select a combination of a plurality of measures according to the time-series transition of the skin state as the measure group.

  According to the skin condition recognition apparatus having the above configuration, the user's skin condition at the time of execution of the user recognized by the first recognition method after the second and subsequent executions of the first recognition method by the measure group selection unit. A combination of a plurality of measures corresponding to the measure executed by the user and the time-series transition of the user's skin condition is selected as the measure group. Thereby, in addition to the skin state at the time of execution of the user recognized by the first recognition method, the influence on the user's skin due to the implementation of the measure is taken into account, and therefore, there is a high probability of being more suitable for the user. A combination of measures can be selected.

In these skin condition recognition devices,
The storage unit stores measures executed by the user and time-series transitions of the user's skin state,
After the first execution of the first recognition method, the measure group selection unit includes the user's skin state at the time of execution recognized by the first recognition method, measures executed by other users, It is preferable to select a combination of a plurality of measures according to the time-series transition of the user's skin state as the measure group.

  According to the skin state recognition device having the above configuration, the measure group selection unit can determine the skin state at the time of execution of the user recognized by the first recognition method after the first execution of the first recognition method. A combination of a plurality of measures corresponding to the measure executed by another user and the time-series transition of the skin condition of the other user is selected as the measure group. The effect on the skin condition due to the implementation of the measure is expected to have a similar effect to some extent although there are variations among users. For this reason, in addition to the skin state at the time of execution of the user recognized by the first recognition method, the influence on the skin of other users due to the implementation of the measure is taken into account, and thus the probability that is more appropriate in view of the skin state A combination of a plurality of measures with high values can be selected.

In the skin condition recognition device of the present invention,
The measure group selection unit receives skin condition request information indicating a request regarding a user's skin condition from the user terminal, and selects a combination of a plurality of measures according to the request indicated in the skin condition request information as the measure group. It is preferable to do.

  According to the skin condition recognition apparatus having the configuration, a combination of a plurality of measures according to a user's request regarding the skin condition is selected as the measure group. By selecting a measure from these measure groups and transmitting measure information indicating the selected measure, the user can be made aware of the measure for realizing the user's request.

In the skin condition recognition device of the present invention,
The measure information transmission unit recognizes an implementation rate of the measure by the user based on information input to the user terminal or information measured by the user terminal, and the implementation rate of the measure is a predetermined implementation rate or less. It is preferable to exclude measures that are from the measure group.

  According to the skin condition recognition device having the configuration, measures with an implementation rate equal to or less than a predetermined implementation rate are excluded from the measure group, and therefore it is possible to avoid repeatedly selecting measures that are difficult for the user to implement.

In the skin condition recognition device of the present invention,
The measure information transmitting unit recognizes the improvement degree of the skin state by the measure by the user based on the user's skin state recognized by the second recognition method, and the improvement degree of the skin state by the implementation of the measure is It is preferable to exclude a measure that is equal to or less than a predetermined improvement degree from the measure group.

  According to the skin condition recognition apparatus having the above configuration, the measure information transmitting unit excludes measures from the measure group that have a skin condition improvement degree equal to or less than a predetermined improvement degree by implementing the measure. It is also avoided that measures that are difficult to improve the skin condition are repeatedly selected.

In the skin condition recognition device of the configuration,
The measure information transmitting unit recognizes the improvement degree of the state of the specific element by the measure by the user based on the state of the specific element that is one or both of the user's body and mind, and by implementing the measure Excluding a measure satisfying at least one of a condition that the degree of improvement of the skin condition is equal to or less than a predetermined degree of improvement and a condition that the degree of improvement of the state of the specific element due to the implementation of the measure is equal to or less than a predetermined degree of improvement preferable.

  According to the skin condition recognition device having the above configuration, the measure information transmission unit makes a condition that the improvement degree of the skin condition by the implementation of the measure is equal to or less than a predetermined improvement degree and the improvement degree of the state of the specific element by the implementation of the measure. Measures that satisfy at least one of the conditions that is less than or equal to a predetermined improvement are excluded from the measure group. As a result, measures for which the degree of improvement in the skin condition resulting from the implementation of the measure exceeds a predetermined degree of improvement, and measures for which the degree of improvement of the state of the specific element resulting from the implementation of the measure exceeds the predetermined degree of improvement remain in the measure group. Therefore, it becomes easy to select a measure that can improve both the skin condition and the state of the specific element.

In the skin condition recognition device of the configuration,
It is preferable that the measure information transmission unit recognizes the improvement degree of the skin condition based on an average skin condition of the user in a predetermined period recognized by the second recognition method.

  According to the skin condition recognition device having the above configuration, the improvement degree of the skin condition is based on the average skin condition of the user in the predetermined period recognized by the second recognition method by the measure information transmission unit. Be recognized. Thereby, even when the recognition accuracy of the second recognition method varies, the recognition accuracy variation can be averaged by recognizing the improvement degree of the skin state based on the average skin state. The improvement degree of the skin condition can be recognized with high accuracy.

In the skin condition recognition device of the present invention,
It is preferable that the measure group selection unit receives measure request information indicating a request regarding a measure of the user from the user terminal, and selects a combination of a plurality of measures corresponding to the measure request information as the measure group.

According to the skin state recognition device having the configuration, the measure group selection unit selects a combination of a plurality of measures in accordance with the user's request as a measure group. This makes it easier for the measure selected from the measure group to be in line with the user's wishes, and as a result, the implementation rate of the measure is improved.

In the skin condition recognition device of the present invention,
It is preferable that the measure group selection unit receives from the user terminal already-implemented measure information indicating a measure already performed by the user, and excludes the measure already performed by the user from the measure group.

  According to the skin condition recognition apparatus having the above configuration, the measure already selected by the user is excluded from the measure group by the measure group selection unit. Therefore, the measure included in the measure group is a measure that the user cannot currently implement. Become. There is a possibility that a measure that the user cannot currently implement is a measure that the user does not recognize. For this reason, information useful for the user can be provided by transmitting measure information indicating such measures to the user terminal.

Explanatory drawing of the utilization form of a skin state recognition system. The block diagram of a skin state recognition apparatus and a user terminal. Explanatory drawing of a series of skin support processing by a skin state recognition apparatus. The 1st flowchart of the process in a skin state recognition apparatus. The 2nd flowchart of the process in a skin state recognition apparatus. The 1st flowchart of the process in a user terminal. The 2nd flowchart of the process in a user terminal. Explanatory drawing of the analysis process of the initial data of the skin, mind, and body by subjective data and objective data. Explanatory drawing of quantification of a body state. Explanatory drawing of quantification of a heart state. FIG. 11A is a diagram showing the relationship between each measure and the improvement tendency of the measure, FIG. 11B is a diagram showing the schedule of each step, and FIG. 11C is the relationship between the desired skin, the subjective state of the skin state, and the objective state. FIG. Explanatory drawing of a progress table based on daily monitoring in the period when skin condition support is carried out. Explanatory drawing of the influence on the skin condition by a special case. Explanatory drawing of the display screen of the improvement degree of the skin state in a user terminal. It is explanatory drawing of the evaluation method of a measure, FIG. 15A shows the evaluation criteria of a measure, and FIG. 15B has shown the example of application of measure evaluation. It is explanatory drawing of the evaluation method of a living and a special case, FIG. 16A shows the evaluation standard of a living and a special case, and FIG. 16B has shown the application example of evaluation of a living and a special case. Explanatory drawing of the determination method of a goal achievement degree. Explanatory drawing of secondary data.

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

[A. Usage of skin condition recognition system]
With reference to FIG. 1, the structure of the skin condition recognition apparatus 10 and the positioning with respect to the system which comprises this invention are demonstrated. The skin condition recognition device 10 is configured by a computer system including a CPU, a memory, various interface circuits, and the like. The skin condition recognition apparatus 10 improves or maintains the skin conditions of a plurality of users U (examples of UA, UB, and UC in FIG. 1) by executing a skin condition support program stored in a memory on the CPU. For executing the processing (skin condition support processing) for the purpose.

  Skin condition recognition device 10 performs data communication with communication terminals (user terminals) 30 of multiple users U (30A, 30B, and 30C are illustrated in FIG. 1) via communication network 1 such as the Internet. Thus, the improvement or maintenance of the skin condition of the user U is supported. A system including the skin condition recognition device 10 and one or a plurality of user terminals 30 corresponds to an example of the “skin condition recognition system” of the present invention.

  A communication terminal 50 (50A, 50B is illustrated in FIG. 1) of a person in charge T (TA, TB is illustrated in FIG. 1) is also connected to the communication network 1. The person in charge T receives, via the communication terminal 50, data including information such as an appropriate skin care method that takes into account the user's U skin features, hobbies, lifestyles, and the like, and the skin condition recognition device 10 and the user terminal 30. To the user U for advice on improving the skin condition. Note that 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, but the entire system including the skin condition recognition device 10, the communication terminal 50 of the person in charge T, and the communication network 1 The advice for improving the skin condition of the user U may be provided to the user terminal 30 of the user U. For example, a method of providing advice to each of the user terminals 30 of the user U by the plurality of persons in charge T via the respective communication terminals 50 may be used.

  Further, the skin condition recognition device 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 next data to another system 60 via the communication network 1 can also be performed.

[B. Configuration of skin condition recognition device and user terminal]
With reference to FIG. 2, the structure of the skin state recognition apparatus 10 and the user terminal 30 is demonstrated. The skin condition recognition device 10 executes a skin condition support program stored in a memory by a CPU, thereby enabling a skin condition recognition unit 11, a measure group selection unit 12, a measure information transmission unit 13, and a secondary data generation unit. 19 functions. The processing by these configurations will be described later. The skin condition recognition device 10 also includes a support DB (database) 20 that holds various data used for the skin condition support process of the user UA. This support DB 20 is developed on a RAM, for example, and can be rewritten by updating subjective and objective data 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. In the present embodiment, since the user terminal 30 is, for example, a smartphone, the camera 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 application 35A for skin condition support (hereinafter referred to as skin support application 35A) held in the memory 36, whereby the user U supports the skin condition recognition apparatus 10 via the skin support application 35A. Can be enjoyed.

  In addition, the user U additionally has a keratin collection tape 37 (in FIG. 1, 37A, 37B, and 37C are illustrated) for acquiring skin cells. The keratin collection tape 37 may be provided to the user U by the person in charge T in advance, or the user U may purchase a commercially available keratin collection tape 37.

  In the following description, for convenience of explanation, a user who is a target of the skin condition improvement or maintenance support process is represented as a user UA, and a user different from “user UA” is represented as “other users UB, UC”. .

[C. A series of processes by the skin condition recognition device]
Next, a series of processes performed by the skin condition recognition device 10 will be described with reference to FIG. The skin condition recognition apparatus 10 has the following functions: “1. goal setting”, “2. schedule determination”, “3. monitoring”, “4. schedule correction”, “5. The process of each step of “goal determination” and “6.2 secondary data generation” is executed according to the flowcharts shown in FIGS. Moreover, the user terminal 30 performs the process by the flowchart shown to FIG.6, 7 according to the process by the skin state recognition apparatus 10 in each process. Below, the process of CPU35 of the skin state recognition apparatus 10 and the user terminal 30 in each process is demonstrated, referring the flowchart shown to FIGS.

  The user UA downloads the program of the skin support application 35A to the user terminal 30 and activates the skin support application 35A in STEP50 of FIG. Then, the user UA makes a registration application to the skin support application 35A.

  The skin condition recognition apparatus 10 recognizes that “the registration application from the user UA has been accepted” when the registration application from the user UA is accepted in STEP 10 of FIG. 4, and the process proceeds to STEP 11. Then, the skin condition support process after STEP 11 is started.

[D. Goal setting process]
The process of “1. goal setting” shown in FIG. 3 is executed by the skin condition recognition unit 11 and the measure group selection unit 12. In step 11 of FIG. 4, the measure group selection unit 12 requests the user terminal 30 to input information for grasping the current skin, body, and heart states of the user UA and the skin state desired by the user UA. Send data.

  In the user terminal 30 that has received the initial information request data, the skin support application 35A determines the current skin, body, and heart states and the skin state desired by the user UA from the user UA in STEP 51 of FIG. Is displayed on the display 31. On the other hand, the user terminal 30 transmits initial user information data including information input by the user UA to the skin condition recognition device 10. The body and mind of the user UA correspond to an example of the specific element of the present invention.

  The skin state recognition unit 11 receives the initial user information data in STEP 11 of FIG. 4 and recognizes the skin, mind, and body states of the user UA recognized from the initial user information data, and the skin state desired by the user UA. The target level (goal) of the skin condition is set based on the above.

  Here, the initial user information data includes subjective data and objective data regarding the skin condition, the body condition, and the mind condition. Although detailed definition will be described later, subjective data is an item determined by the user's subjectivity, and objective data is data based on examination results, image analysis, and fact information. The subjective data of the skin condition is data indicating, for example, 10 levels of satisfaction of the user UA with respect to the current skin condition. The objective data of the skin state is the skin image data of the user UA. Note that the objective data of the skin condition may include analysis data of stratum corneum cells of the user UA collected by the keratin collection tape 37 in addition to the objective data of the skin condition included in the initial user information data. Specifically, the analysis data of the stratum corneum is, for example, data on water retention ability and sebum suitability. In this case, the analysis of the stratum corneum is performed by, for example, the measuring device 45 connected to the user terminal 30, or the image data of the stratum corneum sampling tape 37 is transmitted from the user terminal 30 to the skin condition recognition device 10, The skin condition recognition device 10 side may analyze the image of the keratin collection tape 37 to measure the water retention capacity and sebum suitability.

The satisfaction degree of the user UA is acquired by a questionnaire input in the skin support application 35A. The skin image data is image data acquired by the user UA capturing an image of the face of the user UA with 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 method of the keratin collection tape 37 on the display unit 31 to prompt the user UA to use the keratin collection tape 37 and send it separately. The skin support application 35 </ b> A may prompt the user UA to use the keratin collection tape 37 and capture a skin image, and transmit the captured image to the skin condition recognition device 10.

  As shown in FIG. 8, the skin condition recognition unit 11 sets the initial value of the skin condition, for example, the subjective score is 3, the skin image score is 3, the water retention ability score is 2, and the sebum suitability score is 1. The total value is assigned as the score of the skin condition.

  Recognition of a water retention ability score and a sebum suitability score by analysis of stratum corneum cells corresponds to an example of the “first recognition method” of the present invention. Alternatively or additionally, the first recognition method may be a method of measuring the moisture content of the user's skin with a stratum corneum moisture meter, a method of measuring the sebum amount of the user's skin with a sebum meter, and a user with a specialized tool. Including at least one method of measuring the skin condition of the skin. In addition, in order to periodically recognize the skin of the user UA by the first recognition method, the skin condition recognition unit 11 periodically uses a tool such as a keratin sampling tape 37 or a specialty store on the user terminal 30 of the user UA. A notification such as a message prompting the customer to visit the store is transmitted, and the notification is output to the display 31 of the user terminal 30, thereby prompting the user UA to act. In this case, “periodic” does not need to be strictly equally spaced in time, and may be equally spaced within a range that does not affect the skin condition. For example, in the case where the first recognition method is performed every three months, when the first time is performed on January 1, not only April 1, which is three months later, but instead or in addition, for example, A notification may be transmitted to the user terminal 30 around March 24, one week before, or instead of or in addition, for example, a notification may be sent to the user terminal 30 around April 8, one week later. May be. Also, when providing a service for a long period of time, for example, when you want to examine a fine improvement, set the first recognition method every month, and check the effect of seasonal changes by setting the first recognition method. The recognition timing can be changed, such as setting the first recognition method for each month.

  As an example of specialized tools, analysis of “stains” “wrinkles” “pores” “color unevenness” “porphyrin” “hidden spots” “melanin index” “hemoglobin index” is possible based on color photographs and UV photographs. VISIA (registered trademark) EVOLUTION.

  Another example of a specialized tool is the MOISUTUREMAP MM100, a skin moisture distribution / portable measuring device that quantifies skin moisture distribution and surface morphology by imaging a signal due to capacitance.

  As another example of a specialized tool, there is a cutaneous mechanics measuring device CUTICAN CS100, which uses a probe built in a camera and displays an elastic waveform of 360 degrees (diameter 5 MM) around the skin displacement when the skin is aspirated and opened. can give.

  Other examples of specialized tools include skin viscoelasticity measurement probe, oil content measurement probe and moisture measurement probe, pH measurement probe, transdermal moisture transpiration measurement probe, melanin & erythema measurement probe, skin gloss measurement probe, skin Skin viscoelasticity geodetic measuring devices such as CUTOMETER DUAL MPA580, DERMA UNIT SSC3, MULTIPROBE ADAPTER MPA6, and MULTITI DEVICEDMD4 are examples of skin viscoelasticity geodetic measuring devices that measure various items of skin with a surface temperature measurement probe, a scalp / skin pressing type hardness tester probe, etc.

  Each of the recognition of the subjective score based on the subjective data of the skin state by the questionnaire input and the recognition of the skin image score based on the skin image data of the user UA correspond to an example of the “second recognition method” of the present invention. The second recognition method is a method with lower recognition accuracy of the user's skin condition than the first recognition method based on a professional and scientific examination. In the second recognition method, the skin condition of the user UA may be recognized by one of recognition of a subjective score based on subjective data of the skin condition by questionnaire input and recognition of a skin image score based on the skin image data of the user UA. Different methods may be included. In addition, the second recognition method is performed more frequently than the first recognition method. This is because the use and mailing of the keratin collection tape 37 is troublesome and cumbersome and has an effect on price. For example, the first recognition method is performed every three months, and the second recognition method is performed at an interval (for example, every day) that is shorter than the interval of the first recognition method. The second recognition method is preferably performed at a higher frequency than the first recognition method. In addition, it is preferable that the second recognition method is implemented such that the number of executions of the second recognition method in a predetermined period is greater than the number of executions of the first recognition method.

  The skin condition recognizing unit 11 performs an operation for acquiring or inputting data on which the recognition method is implemented based on the above-described notification or the like in advance in performing the first recognition method or the second recognition method. It is preferable to prompt the user.

  In addition, when the timings of the first recognition method and the second recognition method are overlapped, it is preferable that the timing is performed at the same timing if possible because accurate data can be obtained. However, even if the second recognition method is not performed when the first recognition method is performed, the present invention can be implemented and an effect can be obtained.

  The second recognition method includes a method for recognizing the skin condition of the user UA based on information received from a wearable device attached to the user UA, and a user based on information measured by a simple tool having a lower accuracy than the specialized tool. It may be a method including at least one of methods for recognizing the skin condition of UA.

  As an example of a simple tool, there is a skin moisture checker that is a patch that is attached to a site to be examined on the skin and in which the color of the test part of the patch changes according to the moisture content of the skin 5 to 10 minutes after application. .

  Another example of a simple tool is a patch that is applied to a site where the skin is to be examined, and the state of the adhesive surface of the patch changes according to the amount of sebum on the skin after a predetermined time has elapsed since application. A sebum checker is available.

  The skin state recognizing unit 11 transmits, to the user terminal 30 of the user UA, a notification requesting input of a questionnaire, a notification for prompting imaging of skin, a notification for prompting use of a simple tool, and the like at intervals according to the second recognition method. The user terminal 30 that has received the notification outputs the received notification to the display 31 to prompt the user to perform each operation. The skin condition recognition unit 11 may set the communication interval of the wearable device to the above-described interval by communicating with the wearable device attached to the user UA. At this time, the wearable device may acquire and transmit objective data, and the skin condition recognition unit 11 may recognize the data, or a part of the function of the skin condition recognition unit 11 may be transferred to the calculation unit of the wearable device. May be installed.

  The skin condition recognition unit 11 may be configured to transmit a notification regarding the second recognition method to the user terminal 30 on the day when the notification regarding the first recognition method is transmitted to the user terminal 30. 2 The notification regarding the recognition method may not be transmitted to the user terminal 30.

The body state subjective data and objective data are divided as shown in FIG. Although the detailed definition will be described later, like the subjective data and objective data of the skin, the subjective data is an item determined by the subjectivity of the user UA, and the objective data is data based on examination results, image analysis, and fact information. The subjective data of the body state is acquired when the user UA inputs a questionnaire through the skin support application 35A. The objective data includes the tongue / lips image data of the user UA captured by the user UA using the camera 33 of the user terminal 30, and the user UA measured by the measuring device 45 connected to the connection terminal 40 of the user terminal 30. Measurement data such as blood pressure, arrhythmia, urinary component, blood component, and the like, data such as the number of poor physical conditions such as headache or stiff shoulder obtained by questionnaire input in the skin support application 35A, and fatigue level determination. It should be noted that information on the occurrence of various diseases may be included in the initial user information data in preparation for future development of services other than skin care.

  The subjective data and the objective data of the mental state are divided as shown in FIG. Although the detailed definition will be described later, like the subjective data and objective data of the skin, the subjective data is an item determined by the subjectivity of the user UA, and the objective data is data based on examination results, image analysis, and fact information. Subjective data is acquired by questionnaire input in the skin support application 35A. The objective data is acquired by questionnaire input (frequency of daily laughter, etc.) in the skin support application 35A and measurement by a measuring device (psychological state estimation from pulse monitoring, etc.). In addition, in preparation for the development of services other than skin care in the future, occurrence information of various mental illnesses may be included in the initial user information data.

  In the present embodiment, the skin state recognition unit 11 performs the first recognition method and the second recognition method, and recognizes subjective data and objective data of the skin, body, and mind states of the user UA. For example, in the present embodiment, the skin condition recognition unit 11 receives the questionnaire input of the user UA and outputs it from the user terminal 30 by outputting a questionnaire input screen related to the skin of the user UA on the display 31 of the user terminal 30. The skin condition recognition unit 11 may recognize information indicating the skin condition of the user UA (for example, a skin condition score) based on the questionnaire result, or the function of the skin condition recognition unit 11 may be included in the skin support application 35A. The information indicating the skin condition may be transmitted to the skin condition recognition device 10 by providing a part thereof.

  Similarly, in the present embodiment, the skin condition recognition unit 11 receives the questionnaire input of the user UA by outputting a questionnaire input screen related to the body of the user UA on the display 31 of the user terminal 30. Based on the transmitted questionnaire result, the skin state recognition unit 11 may recognize information indicating the body state of the user UA (for example, a body state score), and the function of the skin state recognition unit 11 is included in the skin support application 35A. The information indicating the body state may be transmitted to the skin state recognition device 10.

  In this embodiment, the skin condition recognition unit 11 receives a questionnaire input of the user UA and outputs it from the user terminal 30 by outputting a questionnaire input screen related to the mind of the user UA on the display 31 of the user terminal 30. The skin state recognition unit 11 may recognize information (for example, a heart state score) indicating the user UA's heart state based on the questionnaire result, and the function of the skin state recognition unit 11 may be included in the skin support application 35A. A part of the information may be sent to the skin condition recognition apparatus 10 to indicate the heart condition.

  Then, the skin condition recognition unit 11 stores the subjective data and objective data of the recognized skin, body, and mind of the user UA in the support DB 20.

  Based on the subjective data and objective data of the skin state, the body state, and the mental state of the user UA recognized as described above from the initial user information data, the skin state recognition unit 11 is indicated by the right triangle in FIG. In addition, initial values of three axes representing the skin state as 1 to 9, the body state as 1 to 6, and the heart state as 1 to 6 are set.

  Further, the measure group selecting unit 12 acquires “skin level to be desired”, “measure category, hope, frequency” and “currently implemented measure” included in the initial user information data. The “satisfying skin level”, “measure category, hope, frequency” and “currently implemented measure” are input by the user UA through the skin support application 35A.

  “Skin level desired” corresponds to “skin condition request information” of the present invention. “Measure category, hope, frequency” corresponds to “measure request information” of the present invention. The “currently implemented measure” corresponds to “already implemented measure information” of the present invention.

  Here, in “Skin Level”, “Skin Level” refers to dryness improvement, wrinkle improvement, sensitive skin improvement, acne improvement, blurring improvement, spot improvement, wrinkle improvement, sagging improvement, dullness improvement, bear improvement, It is a skin condition improvement target selected from face color improvement and elasticity improvement. The “level” is the level of satisfaction of the user UA with respect to the skin condition of each target, and is a level selected by the user in 10 levels from 1 to 10 in the skin support application.

  The support DB 20 stores the improvement tendency of the subjective state of the skin state and the improvement tendency of the objective state associated with each improvement target. For example, as shown in FIG. 11C, “Dry feeling improvement” includes a skin condition subjective condition “dry feeling improvement” and a skin condition objective condition criterion “the difference between water retention ability and sebum suitability is minimized. ".

  For example, when “desired skin” is “improvement of dryness” and the satisfaction level of dryness in the current skin state is 3, it is associated with “improvement of dryness” according to the selection of the user UA. Satisfaction level 5 regarding the subjective state “improvement of dryness” of the user UA's skin state is set as a subjective target level. For example, when the level of satisfaction level of the current skin condition is 3, when the user selects “current level + 2 level”, the target level 5 is set for “dryness improvement”. In addition to or instead of this, the level 5 selected by the user may be set as the target level 5 as it is.

  In addition, the measure group selection unit 12 sets an objective improvement target of the skin condition associated with “dryness improvement”. For example, the measure group selection unit 12 is lower than the water retention capability among the skin conditions of the user UA based on the criterion “minimize the difference between the water retention capability and sebum suitability” associated with “improvement of dryness”. Sebum eligibility value 2 is set as an objective target level.

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

  “Currently implemented measure” is a measure that the user UA has already implemented, and is expressed by the content and frequency or degree of “use a bath”.

[E. Schedule determination process]
The step of “2. Schedule determination” shown in FIG. 3 is executed by the measure group selection unit 12 and the measure information transmission unit 13. The measure group selection unit 12 selects a measure group for achieving a goal (a subjective target level and an objective target level) in STEP 12 of FIG. This selection is performed in consideration of the improvement tendency of the subjective state of the skin state, the improvement tendency of the objective state of the skin state, 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 a pre-registered area or GPS sensor and the date and time acquired from the clock function of the terminal. Predict.

  For example, the measure group selection unit 12 is a season in which the category hope is “behavior at home, eating habits, exercise” and the humidity is predicted to be an average of 50% as in the rainy season. If the level is “dryness” satisfaction level 5 or higher and the objective target level is sebum qualification level 2 or higher, the improvement tendency of the subjective condition includes “improvement of dryness” and the improvement tendency of the objective condition is “sebum qualification Select a measure that includes “improvement” and the category is “behavior, eating habits, exercise” at home, and the suitable surrounding environment is consistent with 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 the like, and may be implemented by other users UB and UC stored in the support DB 20. May be an improvement tendency of the subjective state and an objective state estimated based on a time-series change of the skin state of the other user UB and UC, and the implemented measure and the skin state of the user UA When the time-series changes are stored in the support DB 20, the improvement tendency of the subjective state and the improvement tendency of the objective state estimated based on the information may be used.

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

  In addition, for example, in the support DB 20, the measure “used by the bathtub” performed by each of the other users UB and UC and the subjective state of the skin condition of each of the other users UB and UC before and after the measure is implemented. It is assumed that “satisfaction with dryness” as a time series change is stored.

  At this time, for each of the other users UB and UC, the measure group selecting unit 12 has, for example, the subjective data (dry feeling) of the skin condition on the day before using the bathtub and the day when using the bathtub. (Satisfaction level) is calculated. And the measure group selection part 12 takes the average value of the variation | change_quantity of the average value of the variation | change_quantity of satisfaction about the dry feeling for each other user UB and UC. For example, when the average value of the amount of change in “satisfaction with dryness” 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 “use a bathtub” as “improvement in dryness”. Recognize. The improvement tendency of the objective state can be recognized in the same manner as the improvement tendency of the subjective state.

The measure group selection unit 12 may narrow down the ranges of other users UB and UC to be processed, such as the same age and similar skin conditions, based on the age and skin condition of the user UA.

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

  The measure group selection unit 12 recognizes the improvement tendency of the subjective state and the improvement tendency of the objective state from the subjective data and objective data of the skin state of other users UB and UC in the first schedule determination step of the user UA. In the second schedule determination step of the user UA, the subjective state improvement tendency and the objective state improvement tendency may be recognized from the subjective data and objective data of the user UA's skin state.

  The measure group selection unit 12 recognizes not only the skin state but also the mental state and the body state in the same manner, the improvement tendency of the subjective state and the improvement state of the objective state, A measure may be selected in consideration of an improvement tendency of the objective state.

  The measure group selection unit 12 may exclude the measure having the same content, the same frequency, or the same level as the “currently implemented measure” from the measure group. This is because it is considered that the measures that the user has already taken need not be proposed.

  In the example of FIG. 11A, the measure group selection unit 12 selects a measure group that is a combination of a plurality of measures so as to include “use a bathtub”, “vitamin C intake”, “vegetable intake”, and “walk more than 10,000 steps”. .

  The measure information transmission unit 13 evaluates the priority of the measure according to the “category category, hope, frequency” of the user UA from the measure group, and determines the initial measure according to the priority. FIG. 12 illustrates an example of a schedule in which “use a bathtub”, “vegetable intake”, and “walk more than 10,000 steps” are selected as initial measures. The measure information transmission unit 13 transmits schedule data indicating the contents of the schedule determined in this way to the user terminal 30. For example, the priority is corrected so that the priority of the measure that matches the “measure category, hope, frequency” received from the user terminal 30 is increased, and the measure is selected from the corrected measures according to the priority. The

  The measure information transmission unit 13 also creates a plan for performing each process for a certain period based on the designation of the user UA. In FIG. 11B, goal setting and schedule determination at START are performed, daily monitoring is performed, schedule is corrected every week, a progress graph is created after one month, goal determination and new goal are established at the third month The plan for a series of events to set up is shown. The measure information transmission unit 13 may use a predetermined execution plan for each process for a certain period in addition to or instead of designation by the user UA.

  When the schedule data is received from the skin condition recognition device 10 in STEP 52 of FIG. 6 at the user terminal 30, the skin support application 35A displays the schedule execution table as shown in FIG. 12 and the work content as shown in FIG. 11B. The user UA is encouraged to implement each measure. In the execution table of FIG. 12, the contents of each measure (“use a bathtub”, “vegetable intake”, “walk more than 10,000 steps”) are displayed.

[F. Monitoring process]
The process of “3. monitoring” shown in FIG. 3 is executed by the skin condition recognition unit 11 and the measure information transmission unit 13 for each period set by the user UA on the skin support application 35A (daily in FIG. 11B). . The user UA who has started using the skin support application 35A uses the user terminal 30 to perform daily skin, body, and mind states, the implementation status of the measures specified by the schedule, and users other than the measures specified by the schedule. Enter the implementation status of UA's voluntary actions (actions outside measures).

  The skin support application 35A proceeds to STEP 60 when the skin, body, and heart states are input by the user UA in STEP 53 in FIG. 6, and the skin, body, Current user information data including subjective data and objective data regarding the state of the mind is transmitted to the skin condition recognition device 10 and the process proceeds to STEP54. Note that the skin support application 35 </ b> A proceeds to STEP 54 as it is when the skin, body, and heart states are not input by the user UA in STEP 53 of FIG. 6. The data transmitted here does not include data relating to the stratum corneum cells collected by the keratin collection tape 37.

  Further, the skin support application 35A advances the process to STEP 61 when the execution status of the schedule (execution status of each measure) is input by the user UA in STEP 54 of FIG. 6, and executes the execution status data indicating the execution status of the schedule. It transmits to the skin state recognition apparatus 10, and advances a process to STEP55 of FIG. The skin support application 35A proceeds to STEP 55 as it is when the schedule execution status (execution status of each measure) is not input by the user UA in STEP 54 of FIG.

  Further, the skin support application 35A proceeds to STEP 62 when the implementation status of the off-policy action is input by the user UA in STEP 55 of FIG. 7, and the off-policy action execution data indicating the content of the off-policy action performed. Is transmitted to the skin condition recognition apparatus 10 and the process proceeds to STEP56. It should be noted that the skin support application 35A proceeds to STEP 56 as it is when the implementation status of the non-measure action is not input by the user UA in STEP 55 of FIG. The skin support application 35A may recognize the implementation status of the off-policy action from the data selected by the user U via the touch panel 32 or input data (for example, text data), or input through a microphone or the like. By analyzing the voice data, the implementation status of the off-policy action may be recognized, or the off-policy action based on the data measured by the wearable device communicating with the user terminal 30 or the step counting function of the user terminal 30 You may recognize the implementation status.

  STEP 13 in FIG. 4 to STEP 16 in FIG. 5 and STEP 20 to STEP 22 in FIG. 4 are processes by the measure information transmitting unit 13. The skin condition recognition unit 11 advances the process to STEP 20 when receiving the current user information data from the user terminal 30 in STEP 13, accumulates the current user information data in the support DB 20, and advances the process to STEP 14. The skin condition recognition unit 11 proceeds to STEP 14 as it is when it does not receive the current user information data from the user terminal 30 at STEP 13.

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

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

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

  Here, for example, as shown in FIG. 12, the progress chart of the schedule includes, from the top, the level of the skin condition (here, dry skin), the level of the body condition, the level of the mental condition, and the measure (the vegetable used in the bathtub) The implementation status of ingestion (walking more than 10,000 steps), living information (vegetable intake, water intake), and living special cases are displayed on a daily basis.

  In the user terminal 30, the skin support application 35 </ b> A advances the process to STEP 63 when receiving the progress table data transmitted from the skin condition recognition device 10 in STEP 56 of FIG. 7, and holds the progress table data in the memory 36. The skin support application 35 </ b> A displays the progress table shown in FIG. 12 on the display 31 of the user terminal 30 using the progress table data stored in the memory 36.

  In addition to the progress table data, the skin support application 35A recognizes the initial user information data, the current user information data, and the execution status data of the user UA stored in the support DB 20 of the skin condition recognition device 10 recognized through communication. Information indicating the transition or change of each state of the skin, body, and mind of the user UA is displayed on the display unit 31 of the user terminal 30 using the non-measure action execution data and the like.

  For example, as shown in FIG. 13, the skin support application 35 </ b> A performs actions of the user UA (change of face washing method, massaged, lack of sleep, etc.) other than the measures based on the schedule, and the user's physical condition (physiology, poor physical condition) , Mental disorder, etc.) and changes in the skin condition of the user UA are displayed on the display 31 in a time series graph in units of days.

  Further, as shown in FIG. 14, the skin support application 35 </ b> A changes the evaluation value of the skin condition including the horny state of the user UA, the psychological state, the satisfaction degree of the skin care, and the usage value of the cosmetics, on a monthly basis. The contrasted radar chart is displayed on the display 31.

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

[G. Schedule correction]
The process of “4. schedule correction” illustrated in FIG. 3 is executed by the measure information transmission 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. 5 are processes by the measure information transmitting unit 13.

  The measure information transmission unit 13 is incorporated in the target achievement level and schedule of the user UA skin state based on the initial user information data, current user information data, execution status data, and the like of the user UA accumulated in the support DB 20 in STEP 17. The degree of execution of each measure and the effect of each measure are evaluated.

  The measure information transmission unit 13 extracts the correlation between the skin state and the body or mind state using the measure judgment criteria shown in FIG. 15A, and each measure incorporated in the schedule based on this correlation Continuation, exclusion from the measure group, discontinuation of the measure, change to another measure.

  In the evaluation criteria of FIG. 15A, four items of presence / absence of execution, influence on the skin, influence on the body, influence on the mind are used as the determination items, and the implementation rate exceeds the predetermined implementation rate, which has a positive effect on the skin. A measure that does not have a bad influence on the body and mind is judged as A and is determined to continue. A good effect on the skin, body, and mind may be a predetermined change (for example, an increase in the amount of moisture in the skin), or a change that causes the subjective value or objective value to approach the target level. May be. The bad influence on the skin, body and mind may be a predetermined change (for example, a decrease in the amount of moisture in the skin), or a change in which the subjective value or objective value deviates from the target level. There may be. In FIG. 15A, a measure whose implementation rate exceeds a predetermined implementation rate is denoted as “implementation”, and a measure whose implementation rate is equal to or less than the predetermined implementation rate is denoted as “non-execution”. The same applies to FIGS. 12 and 15B.

If the timing of the impact of the measure and the period during which the impact continues are determined for each measure, the measure information transmission unit 13 may determine the impact of each measure based on the timing of the impact and the duration of the impact. Good.

  For example, if the effect on the skin, the influence on the body, and the influence on the mind of “use a bathtub” is affected the next day, and it is determined that it will continue for one day, the measure information transmission unit 13 may, for example, It is determined that the influence of “Used on a bathtub” on March 15 is reflected in each state on December 16.

  Further, when it is determined that the effect of “vegetable intake” on the skin, the effect on the body, and the effect on the mind will be affected after one week and will continue for three days, the measure information transmission unit 13 may, for example, It is determined that the influence of “vegetable intake” on the 15th of the month is reflected in each state from December 22 to December 24.

  On the other hand, measures that are implemented and have a positive effect on the skin, but have a negative effect on either the body or the mind, are evaluated as B and are determined to be canceled or changed to another measure. In addition, since it is considered that a measure for which the implementation rate is equal to or less than the predetermined implementation rate has a large load on the user UA, it is canceled as a C evaluation or another measure (for example, a measure that reduces the load on the user UA or another type of measure). It is judged to be a change to measures.

  The measure information transmission unit 13 may evaluate whether there is a good or bad influence on the skin, body, and mind by implementing each measure for only one day, and in a certain period such as several days or weeks By implementing each measure, it may be evaluated whether there is a good or bad influence on the skin, body and mind. When evaluating in a certain period, for example, the measure information transmitting unit 13 sets B evaluation when any state is adversely affected at a certain rate, C evaluation when the implementation rate is below a certain rate, and otherwise In the case of A, it is good also as A evaluation. Instead of this, for example, the measure information transmission unit 13 may perform the B evaluation when the average value of the satisfaction degree in any state in a certain period is equal to or less than a predetermined value.

  Further, when the improvement degree of the skin condition score shown in FIG. 8 is equal to or less than a predetermined improvement degree, the measure information transmission unit 13 performs a measure in which the improvement degree of the skin condition score is equal to or less than the predetermined improvement degree. It may be excluded from the measure group. The measure information transmission unit 13 measures a measure in which the improvement level of the body state or the mental state score is equal to or lower than the predetermined improvement level when the improvement level of the body state or the mental state score is equal to or lower than the predetermined improvement level. May be excluded. Here, the predetermined degree of improvement is not necessarily positive, and may be zero or negative.

  FIG. 15B shows an example in which the evaluation standard shown in FIG. 15A is applied to a measure in the present embodiment (taken by a bathtub, ingesting vegetables, walking more than 10,000 steps). According to FIG. 15B, the measure information transmission unit 13 decides to continue on the next schedule as “A” for “use on a bathtub”, and exclude from the measure group as “B” for “vegetable intake”. Decided to cancel the schedule or change to other measures, and for “walk more than 10,000 steps” as C evaluation, exclude from the measure group, cancel the next schedule or change to other measures Has been decided.

  The measure information transmission unit 13 determines, for each combination of these measures, the influence of the plurality of measures being performed. For example, if the combination of “use a bath” and “vegetable intake” is B evaluation or C evaluation, the measure information transmission unit 13 should only use “use a bath” or “vegetable intake” alone. Or you may change so that it may be set as the combination of one of these measures and another measure.

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

  Next, in step 19, the measure information transmitting unit 13 is incorporated in the schedule of each non-measure action (scheduled by the user UA) based on the initial user information data, the current user information data, the non-measure action execution data, and the like. Evaluate actions taken by users in addition to measures.

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

  Then, when “there is a good effect on any of skin, body, and mind, and there is no adverse effect on any of them”, implementation is recommended as D evaluation. On the other hand, in the case of “there is a bad influence on any of skin, body and mind”, an E evaluation is given and a prohibition is proposed. In addition, in the case of “no effect on skin, body, or mind”, the evaluation is F and implementation is not recommended.

  FIG. 16B shows an example in which the evaluation standard shown in FIG. 16A is applied to the action outside the measure in the present embodiment (massage is received and a large amount of chocolate is ingested). As shown in FIG. 16B, the measure information transmission unit 13 determines the recommendation for the implementation on the next schedule as the D evaluation for “receiving massage”. In addition, regarding “a large amount of chocolate intake”, as an E evaluation, a proposal for a measure for stopping at the next schedule (for example, an alternative to ingest Japanese sweets) has been decided.

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

  On the other hand, when the measure information transmitting unit 13 determines the proposal of prohibition, the processing proceeds from STEP 31 to STEP 32, and transmits the non-measure action prohibition data for proposing prohibition of the non-measure action to the user terminal 30, and FIG. The process proceeds to STEP13.

  Further, when there is no action outside the measure for proposing recommendation or prohibition, the measure information transmission unit 13 proceeds from STEP 20 to STEP 13 in FIG. 4. In addition, when there is a substitute action in the action outside the measure for proposing prohibition, the action prohibition data outside the measure for proposing a change to the substitute action may be transmitted to the user terminal 30 instead of the proposal for the prohibition.

  In the user terminal 30, when receiving the schedule correction data from the skin condition recognition device 10 in STEP57 of FIG. 7, the skin support application 35A proceeds to STEP64 and corrects the schedule based on the schedule correction data. Then, the skin support application 35 </ b> A updates the schedule data held in the memory 36 and advances the process to STEP 58.

In step 58 of FIG. 7, the skin support application 35 </ b> A proceeds to step 65 when receiving the non-measure action recommendation data or the non-measure action prohibition data from the skin condition recognition device 10, and proceeds to STEP 65 according to the received data. A screen for informing the user of the recommended or prohibited action is displayed on the display 31 of the user terminal 30. This notification may be performed, for example, by displaying a notification message on the progress table shown in FIG. Moreover, you may correct a schedule as a new measure for the recommended action outside the measure.

[H. Goal judging process]
The step of “5. Goal determination” shown in FIG. 3 is performed for each period set by the user UA on the skin support application 35A (three months after START in FIG. 11B), the skin condition recognition unit 11, and the measure group This is executed by the selection unit 12 and the measure information transmission unit 13.

  The skin support application 35 </ b> A displays on the display 31 of the user terminal 30 a message prompting the use of the keratin collection tape 37 and the mailing of the keratin collection tape 37.

  The skin condition recognizing unit 11 recognizes an objective value (water retention ability, sebum suitability, etc.) of the skin condition based on information obtained from the keratin sampling tape 37 sent by mail.

  In addition, the skin support application 35A displays a message prompting the use of the answer to the questionnaire, imaging of the skin, and the use of the keratin collection tape 37 on the display 31 of the user terminal 30, and transmits the obtained information.

  The skin condition recognition unit 11 recognizes the subjective score of the dryness of the skin and the image score of the skin based on the information obtained from the information obtained from the skin support application 35A.

  Further, the skin condition recognition unit 11 recognizes the user's skin condition recognized in the initial stage (the execution date of the first recognition method) by the first recognition method and the initial stage (the execution date of the first recognition method) by the second recognition method. The score of the user's skin condition may be corrected based on the user's skin condition and the user's skin condition recognized by the second recognition method on the non-execution date of the first recognition method.

  For example, the skin condition recognition unit 11 acquires the coefficient by dividing the initial water retention ability score by the sum of the subjective score of the initial dryness of the skin and the image score of the skin. Then, the skin condition recognition unit 11 estimates the latest water retention ability score by multiplying the sum of the subjective score of the latest skin dryness and the image score of the skin by the coefficient. Similarly, the skin condition recognition unit 11 can estimate sebum suitability. For example, the skin condition recognition unit 11 calculates a correlation coefficient between each score of the subjective score, the image score, the water retention ability score, and the sebum suitability score based on the data of all users, for example. One or both of the water retention ability score and the sebum suitability score may be estimated from one or both of the subjective score and the image score using the relationship number.

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

  In the example of FIG. 17, since the subjective value level of dryness has increased from 3 to 5 in 3 months, it is determined to be achieved (◯), and the objective image value is 3 to 4 in 3 months for the skin image score. Since the water retention capacity is maintained at 2 and the sebum suitability is increased from 1 to 2, it is 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 total. In addition to these, when both the subjective value and the objective value have reached the target level, it may be determined as achievement (◯). Also, the goal achievement level may be determined by calculating one value (for example, the sum of the subjective value and the objective value) based on the subjective value and the objective value, and comparing it with the target level.

  The skin condition recognition unit 11 and the measure group selection unit 12 re-execute the “1. goal setting” step shown in FIG. 3 in order to set a new goal when the goal is achieved. The skin condition recognizing unit 11 and the measure group selecting unit 12 may perform the “2. schedule determination” step when the goal is not reached, or “1. goal setting” according to the user's desire or progress. The process may be performed again.

[I. Secondary data generation]
The process of “6.2 secondary data generation” shown in FIG. 3 is executed by the secondary data generation unit 19. The secondary data generation unit 19 includes various types of data (hereinafter referred to as individual users) such as initial user information data, stratum corneum cell analysis data, current user information data, execution status data, non-measure action execution data transmitted from a plurality of users U. Data) is 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. 18, the characteristics of each user (gender, age, residence, preference, lifestyle, etc.) ), Targets for improvement of support (dryness, wrinkle, sensitivity, acne, sensation, etc.), measures proposed by the schedule (eg, use of a bathtub, ingestion of vegetables, walking more than 10,000 steps), and skin resulting from the implementation of the measures, Secondary data that correlates changes in each state of the body and mind is generated.

  The secondary data generation unit 19 also provides secondary data that associates the characteristics of each user with the influence of each state of the skin, body, and mind due to the implementation of the off-policy action, as in FIG. Generate.

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

  In the process of “4. Schedule correction” in FIG. 3 described above, the measure information transmission unit 13 changes the secondary data when changing the schedule according to the transition of each state of the skin, body, and mind of the user UA. The schedule can be changed to a plan that incorporates more effective measures or non-measure actions.

In addition, secondary data can be used effectively to support skin conditions and for marketing purposes targeting users with certain characteristics (for example, women in their 30s living in Tokyo, etc.). Can also be used. Therefore, the secondary data may be provided to the other system 60 shown in FIG.
(Other embodiments)
The present invention is also realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

  The measure group selection unit 12 recognizes the user's skin or constitution based on at least the information on the user's skin state recognized by the first recognition method, and selects a measure group corresponding to the user's skin or constitution. You may select as a measure group.

DESCRIPTION OF SYMBOLS 1 ... Communication network, 10 ... Skin condition recognition apparatus, 11 ... Skin condition recognition part, 12 ... Measure group selection part, 13 ... Measure information transmission part, 19 ... Secondary data generation part, 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 (22)

A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognition unit periodically executes the first recognition method and executes the second recognition method at an interval shorter than an interval of execution of the first recognition method. apparatus. A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognizing unit periodically executes the first recognition method, and performs the second recognition method so that the number of executions of the second recognition method in a predetermined period is greater than the number of executions of the first recognition method. A skin condition recognition apparatus characterized by executing a recognition method. A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognition unit performs the first recognition method periodically and executes the second recognition method at a frequency higher than the execution frequency of the first recognition method. . A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognizing unit periodically executes the first recognition method and executes the second recognition method at a timing different from the first recognition method in addition to the execution timing of the first recognition method. Skin condition recognition device characterized by. In the skin condition recognition device according to any one of claims 1 to 4,
The skin condition recognition unit executes the second recognition method on both the execution date of the first recognition method and the non-execution date of the first recognition method, and the first recognition method uses the first recognition method. Based on the data recognized on the execution date, the data recognized on the execution date of the first recognition method by the second recognition method, and the data recognized by the second recognition method on the non-execution date of the first recognition method. A skin condition recognition apparatus for recognizing a user's skin condition on a non-execution day of the first recognition method.   The skin condition recognition apparatus according to any one of claims 1 to 5, wherein the first recognition method includes a method of analyzing data indicating a state of a cell on the surface of the user's skin acquired by a tape. A skin condition recognition device. In the skin condition recognition device according to any one of claims 1 to 6,
The first recognition method includes a method for recognizing a user's skin condition based on data measured by a specialized tool. In the skin condition recognition device according to any one of claims 1 to 7,
The second recognition method is a method of recognizing a user's skin state based on an answer to a questionnaire about evaluation of the user's skin state input at the user terminal, and a user's skin based on an image of the skin imaged at the user terminal. A method for recognizing a skin condition, a method for recognizing a user's skin condition based on information received from a wearable device worn by the user, and a user's skin based on information measured by a simple tool that is less accurate than a specialized tool. A skin condition recognition device comprising at least one of methods for recognizing a condition. In the skin condition recognition device according to any one of claims 1 to 8,
The first recognition method includes at least a method for analyzing a state of a cell on a surface of a user's skin acquired by a keratin sampling tape. In the skin condition recognition device according to any one of claims 1 to 9,
A storage unit for storing a plurality of measures;
After the execution of the first recognition method, a combination of a plurality of measures according to the user's skin condition at the time of execution of the first recognition method recognized by the first recognition method among the plurality of measures. A measure group selection section for selecting a measure group;
Each time the second recognition method is executed once or a plurality of times, a measure corresponding to the latest skin condition of the user recognized by the second recognition method is selected from the measure group, and the selected measure is indicated. A skin condition recognition device comprising: a measure information transmitting unit that transmits measure information to a user terminal. The skin condition recognition apparatus according to claim 10, wherein
The storage unit stores measures executed by the user and time-series transitions of the user's skin state,
The measure group selection unit includes the user's skin state at the time of execution of the user recognized by the first recognition method, the measure executed by the user, and the user after the second and subsequent executions of the first recognition method. A skin condition recognition apparatus, wherein a combination of a plurality of measures corresponding to a time series transition of the skin state is selected as the measure group. The skin condition recognition device according to claim 10 or 11,
The storage unit stores measures executed by the user and time-series transitions of the user's skin state,
After the first execution of the first recognition method, the measure group selection unit, the user's skin state at the time of execution recognized by the first recognition method, measures executed by other users, and other A skin condition recognition apparatus, wherein a combination of a plurality of measures corresponding to a time-series transition of a user's skin state is selected as the measure group. The skin condition recognition device according to any one of claims 10 to 12,
The measure information transmitting unit recognizes the improvement degree of the skin state by the measure by the user based on the skin condition of the user recognized by the second recognition method, and the improvement degree of the measure is a predetermined improvement degree A skin condition recognition apparatus characterized in that the following measures are excluded from the measure group. The skin condition recognition device according to claim 13,
The measure information transmitting unit recognizes an improvement degree of the skin condition based on an average skin condition of the user in a predetermined period recognized by the second recognition method. . A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognition unit periodically executes the first recognition method and executes the second recognition method at an interval shorter than an interval of execution of the first recognition method. system. A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognizing unit periodically executes the first recognition method, and performs the second recognition method so that the number of executions of the second recognition method in a predetermined period is greater than the number of executions of the first recognition method. A skin condition recognition system characterized by executing a recognition method. A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognizing unit periodically executes the first recognition method and executes the second recognition method at a frequency higher than an execution frequency of the first recognition method. . A skin condition recognition unit for recognizing a user's skin condition by one or both of the first recognition method and the second recognition method;
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognizing unit periodically executes the first recognition method and executes the second recognition method at a timing different from the first recognition method in addition to the execution timing of the first recognition method. Skin condition recognition system characterized by A control method for an apparatus including a skin condition recognition unit that recognizes a user's skin condition by one or both of a first recognition method and a second recognition method,
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognition unit includes a step of periodically executing the first recognition method and executing the second recognition method at an interval shorter than an interval of execution of the first recognition method. Control method of skin condition recognition apparatus. A control method for an apparatus including a skin condition recognition unit that recognizes a user's skin condition by one or both of a first recognition method and a second recognition method,
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognizing unit periodically executes the first recognition method, and the second recognition method is performed more frequently than the first recognition method in a predetermined period. A control method for a skin condition recognition device, comprising a step of executing a recognition method. A control method for an apparatus including a skin condition recognition unit that recognizes a user's skin condition by one or both of a first recognition method and a second recognition method,
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognition unit includes a step of periodically executing the first recognition method and executing the second recognition method at a frequency higher than an execution frequency of the first recognition method. A method for controlling the state recognition device. A control method for an apparatus including a skin condition recognition unit that recognizes a user's skin condition by one or both of a first recognition method and a second recognition method,
The second recognition method is a method with lower recognition accuracy of the user's skin state than the first recognition method,
The skin condition recognition unit periodically executes the first recognition method and executes the second recognition method at a timing different from the first recognition method in addition to the execution timing of the first recognition method. The control method of the skin state recognition apparatus characterized by including.