JP2017182264A - Health tuning support system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine in an overall state, a plus element, attention element, economical burden element in use of a health food, and provide information of a more suitable health food according to a life environment of a user.SOLUTION: A determination system for determining suitability of a health food to a user comprises: health food data acquisition means 101 for acquiring health food data including an active ingredient of the health food, a content, an allergic component, a quotation, and acquisition ease; and user data acquisition means 110 for acquiring user data containing life log data which is a record of a user's daily life, and medical examination data of a user on a medical institution. The determination system comprises: score calculation means 132 for performing weighting of the active ingredient included in the health food, and calculating a score (merit score) of the plus element of the health food, a score of the attention element (alert score), and a score of the economical burden element (burden score); and determination means 133 for determining suitability based on the calculated score.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a system for supporting health management through the use of health foods and supplements.

  In recent years, the use of health foods and supplements has expanded. According to Non-Patent Document 1, health foods and supplements are used not only for health maintenance, nutritional supplementation, fatigue recovery, diet, disease prevention, but 5% is used for disease treatment purposes. Sometimes. Information sources for using health foods and supplements include product advertisements, information obtained from familiar people such as family members, friends and acquaintances, and information on TVs and newspapers. Although there are many stores, recently, those via the Internet and mail order routes are also increasing.

  In this way, the world is full of various health foods and supplements, but it is not easy for each individual to obtain information on health foods and supplements suitable for them. For this reason, systems for providing supplement information are known.

  For example, Patent Document 1 discloses a system that provides information on the nutritional status of a subject based on subjective symptoms (inquiry results) and objective data (component analysis results) that do not appear as subjective symptoms, information on supplements, and the like. Is disclosed. More specifically, this system analyzes each individual's nutritional status and nutrients to be ingested based on information obtained through interviews and nail analysis, etc., and information on supplements suitable for each individual based on the analysis results. I will provide a.

  Further, Patent Document 2 can provide an optimal effective amount of supplements for each subject using the results of various tests including genetic testing and blood biochemical testing of the subject. A supplement delivery system is disclosed. This system includes a personal database that stores test results such as genetic tests performed on the subject, and a master database that includes gene databases that store potential disease risk information related to the gene, It has a supplement prescription creation means for collating a test result such as a genetic test with corresponding information in the master database, determining a deficient nutrient component and its effective amount, and creating a supplement prescription.

JP 2005-202833 A JP 2011-204194 A

Ministry of Health, Labor and Welfare, “Diversified health foods”, [online], [March 18, 2016 search], Internet, <URL: http://www.mhlw.go.jp/topics/bukyoku/iyaku/syoku- anzen / dl / pamph_healthfood_d.pdf>

  By the way, information on health foods and supplements that are really suitable for individuals includes not only positive elements such as the efficacy of active ingredients, but also cautionary elements such as additives and allergic ingredients, prices, purchase units, and ease of purchase. Comprehensive judgment of factors that would be psychologically burdensome (including economic burden), taking into account user-side factors such as the user's eating habits, living environment, and lifestyle Need to be done. A system that advises health foods and supplements suitable for their health management is desired.

  In the present invention, in view of the above-described problems, positive factors, caution factors, and psychological burden factors are comprehensively determined for the use of health foods and supplements, and more appropriate depending on the living environment of the user. The purpose is to provide information on health foods and supplements.

In order to solve the above problems, the present invention provides the following solution.
(1) In the first aspect of the present invention, a determination server for determining the suitability of a health food for a user, the health including the active ingredient, content, allergic ingredients, price, and availability of the health food Health data acquisition means for acquiring food data; user data acquisition means for acquiring user data including life log data that is a record of daily life of the user and examination data in the user's medical institution; Based on the acquired user data, weighting means for weighting each active ingredient contained in the health food, and on the basis of the acquired user data and weighting for each active ingredient, plus elements of the health food A score calculation means for calculating a score of an attention element and a score of a psychological burden element based on the acquired user data; Characterized in that it comprises a determination means for determining the compatibility based on the calculated score.

(2) In the configuration of (1), the determination unit may present a combination of a supplement and a health food other than the supplement together with the price.

(3) In the configuration of (1) or (2), the user data acquisition unit includes a life log data acquisition unit that acquires the life log data, and the life log data acquisition unit includes the life log data acquisition unit, You may make it include the inquiry means which acquires the reply of the inquiry with respect to a user, the measurement apparatus which measures physical condition data, and the wearable apparatus with which the said user is mounted | worn and records life data.

(4) Moreover, in the above configurations (1) to (3), the user data acquisition unit includes a net browsing history data acquisition unit, analyzes the acquired browsing history data, and relates to the food of the user. You may make it provide the preference extraction means to extract a preference.

(5) In the above configurations (1) to (4), the user data acquisition means includes household account book data acquisition means, and extracts food expenditure and health food expenditure from the acquired household account data. You may make it provide the food related expenditure extraction means to do.

(6) The second aspect of the present invention is a method for determining the suitability of a health food for a user, including the active ingredient, content, allergic ingredients, price, and availability of the health food. Acquiring health food data; acquiring user data including life log data that is a record of daily life of the user and examination data at the user's medical institution; and the acquired user data Based on the weighting for each active ingredient contained in the health food, calculating the positive factor score of the health food based on the acquired user data and the weighting for each active ingredient, A step of calculating a score of an attention element and a score of a psychological burden element based on the acquired user data, and the calculated score Zui and characterized in that it comprises a, determining the suitability.

(7) Further, in the third aspect of the present invention, there is provided a program for determining the suitability of a health food for a user, the active ingredient of the health food, the content, the allergic ingredients, the price, and the availability. Acquiring health food data including: life log data which is a record of daily life of the user and user data including medical examination data at the user's medical institution; and the acquired user Weighting each active ingredient contained in the health food based on the data, and calculating a positive factor score of the health food based on the acquired user data and weighting for each active ingredient Calculating a score of an attention element and a score of a psychological burden element based on the acquired user data, and the calculated It was based on the score, characterized in that to execute, and determining the suitability of the computer.

  According to the present invention, regarding the use of health foods and supplements, positive factors, attention factors, and psychological burden factors are comprehensively determined, and more appropriate information on health foods and supplements according to the living environment of the user. Can be provided.

It is a figure which shows the basic image of the health tuning assistance system which concerns on embodiment of this invention. It is a figure which shows the function structure of the healthy seafood score determination server which concerns on embodiment of this invention. It is a figure which shows the list of the user data which can be utilized by this system. It is a figure which shows the processing flow of a healthy seafood score determination process. It is a figure which shows the example of scoring of the health food regarding eye strain. It is a figure which shows the example of scoring of the health food regarding obesity. It is a figure which shows the example of the screen which recommends the combination of health food. It is a figure which shows another example of the screen which recommends the combination of health food.

  DESCRIPTION OF EMBODIMENTS Hereinafter, embodiments for carrying out the present invention (hereinafter referred to as embodiments) will be described in detail with reference to the accompanying drawings. In the subsequent drawings, the same numbers or symbols are assigned to the same elements throughout the description of the embodiments.

  In the following, “health food” (or “healthy seafood”) refers to all foods that contribute to the maintenance and promotion of health, and “supplement” generally refers to tablets and capsules in which specific ingredients are concentrated. Products, but also include forms such as beverages and snacks. Since a supplement is considered to be one of health foods, unless otherwise specified, the term “health food” includes supplements.

(Basic image)
FIG. 1 is a diagram showing a concept of a basic configuration of a health tuning support system (hereinafter referred to as the present system) according to an embodiment of the present invention. This system determines the suitability of health foods and supplements and supports user health management and adjustment (health tuning). As mentioned above, information on supplements that are suitable for me is not only a positive factor such as the efficacy of active ingredients, but also a cautious factor such as additives, safety, allergic ingredients, and psychological burden. It is necessary to make a comprehensive judgment in consideration of a wider range of factors such as various burden factors (price, purchase unit, ease of purchase, etc.). Even if it is effective, the price is high, allergic ingredients are included, the purchase unit is decided, the access to the sales base is bad, the delivery time is long, the product is changed according to the situation This is because if the user has difficulty adjusting the amount, the user cannot use it safely and continuously. It is also necessary to consider user preferences and living environments. This system integrates health foods by taking into account not only the ingredients and effectiveness data of health foods (hereinafter referred to as supplements) but also various user data (hereinafter referred to as user data). It is determined automatically and presented to the user.

  This system provides health food data as positive factors such as varieties / production areas, ingredient content, effectiveness, etc. that are related to efficacy (referred to as “merit data”), and additives that are related to safety , Data that is a caution element such as allergic ingredients (called “alert data”), and data related to price, purchase unit, and availability (ease of buying) that are psychological burdens (called “burden data”) ) Are collected and stored in respective databases (storage means).

  In addition, this system acquires lifestyle data, lifestyle habits / behavior patterns, other daily life data (hereinafter referred to as “life log data”), net browsing history as user data, Record. It is also possible to obtain examination data, disease history data, genetic data, etc. obtained from medical institutions. It is also possible to obtain data related to the eating habits of the user's household account book data in cooperation with the household account book program installed on the user's PC or the like. These data may be input by the user himself / herself in the form of answering the questionnaire, or may be acquired from measuring devices for various physical condition data and systems of medical institutions.

  In this system, merit data obtained from these health food data, alert data, merit score corresponding to Baden data, alert score, Baden score, and the total of the scores are weighted to the user data obtained from the user side Then, the calculated health food score (also referred to as “healthy seafood score”) is determined, and the suitability of the health food is presented to the user.

(Functional configuration)
FIG. 2 is a diagram illustrating a functional configuration of the healthy food score determination server according to the embodiment of the present invention. In this figure, the image diagram of FIG. 1 is shown in detail as a functional block of the server, and an arrow between the functional blocks indicates a data flow direction or a process flow direction.

  This system is mainly processed by the healthy score determination server 100 (hereinafter simply referred to as “determination server”). The determination server includes health food data acquisition means 101 and user data acquisition means 110 as data input means.

  The determination server also includes merit data storage means 102, alert data storage means 103, and baden data storage means 104 as a health food database. In addition, as a user data database, browsing history data storage means 115, life log data storage means 116, examination data storage means 117, and household account book data storage means 118 are provided. In addition, the determination server, as the above data processing means, preference extraction means 121, user data classification means 123, food related expenditure extraction means 122, weighting means 131, score calculation means 132, determination means 133, determination result storage means 134 and advice generation means 135. Hereinafter, each means will be described in order.

  The health food data acquisition means 101 obtains data such as varieties and production areas of health foods, content of active ingredients, additives / allergic ingredients, price / sales form, etc. from product advertisements, manufacturers, dealers, information on the Internet, etc. get. Of the acquired data, data that is a plus element (such as the content of active ingredients) is stored in the merit data storage unit 102. Further, data (additives, allergic components, etc.) serving as caution elements are stored in the alert data storage means 103. Further, data of factors that are economical burdens (price, purchase unit in sales form, ease of purchase, etc.) are stored in the Baden data storage means 104. In particular, the price and availability of natural foods vary depending on the season and region, so it is acquired for each season and region. In addition, when the health food is a natural food, data on the varieties and production areas are also stored in the merit data storage means 102. However, depending on the case, the product / production area data may be stored in the alert data storage means 103.

  The user data acquisition unit 110 includes a net browsing history data acquisition unit 111, a life log data acquisition unit 112, a screening data acquisition unit 113, and a household account book data acquisition unit 114.

  The net browsing history data acquisition unit 111 acquires a user's Internet browsing history from the user's terminal.

  The life log data acquisition unit 112 acquires data related to the life of the user. The life log data may be input in the form that the user answers Yes / No to the inquiry means prepared by the system, or may be input directly in text. In addition, measuring devices for measuring body temperature data such as blood pressure monitors, thermometers, exercise meter, and wearable devices attached to the user's body can be connected to the user's terminal (PC, smartphone, tablet terminal, etc.) via the Internet. ) To obtain the life log data automatically or semi-automatically via the user terminal.

  The screening data acquisition unit 113 acquires screening data. The screening data may be input by the user based on the data from the medical institution, but the system of the medical institution and the user terminal are connected via a network, and the necessary screening data is captured in the user terminal. Also good.

  The household account book data acquisition means 114 acquires the user's household account book data from a household account book program installed in the user's terminal or the like.

  The data acquired by each of the acquisition means is collected in each database of browsing history data storage means 115, life log data storage means 116, examination data storage means 117, and household account book data storage means 118, respectively.

  FIG. 3 shows a list of data that can be used in this system as user data. User data includes attribute data, browsing history data, life log data, examination data, and household account book data. However, the attribute data may be included in the life log data.

  The browsing history data is a history of a site that a user browses on a daily basis, and stores browsing date, site name, search keyword, and the like. User preferences can be extracted from such browsing history data and used for health food advice. For example, if you are searching for supplements, it is recommended that you take supplements. If you are using a home delivery service for ingredients and vegetables, you may recommend taking vegetables. For example, it recommends what the mountaineer is using, and uses it as supplementary data when recommending health food.

  The attribute data is data relating to static attributes of individual users such as age, sex, residential area, address, occupation, family structure, and the like. Life log data is dynamic data related to daily life of users. Wake-up / sleeping time, sleeping hours, working hours, work types (in-house work, out-of-office work, desk work, standing work), number of eating outs per month It is desirable to include the daily TV viewing time, PC and smartphone usage time, average alcohol consumption, smoking amount, and the like. Also, if data can be obtained from various measuring instruments such as blood pressure monitors, pedometers, activity meters, etc., the number of steps, exercise calorie consumption, body temperature, fingertip body temperature, blood pressure, pulse, etc. measured by the measuring instrument are received. Should be included in the data. In addition, it is desirable to include data on eating habits, for example, whether the breakfast is bread or rice or daily drinks.

  Screening data includes height, weight, body fat percentage, blood pressure, pulse, blood test results, brain age, blood vessel age, skin age, allergic components, and the like. The medical examination data may include disease history data and genetic data. In addition, it is desirable that life log data or examination data include food or ingredients with allergies and information on whether or not pregnant.

  Household account book data is data obtained by extracting from the household account book data on monthly expenses of users, especially food expenses, desserts / confectionery, liquor / tobacco, health food / supplements, medical / medicine, etc. However, if the user is not a single person but lives in a family and has a common household, it is necessary for the user to convert the expense into the user's own expense.

  Returning to the description of FIG. 2, the description of each means will be continued. The preference extraction unit 121 analyzes the data in the browsing history data storage unit 115 and extracts the user's preference. The food-related expenditure extracting unit 122 analyzes the data in the household account book data storage unit 118 and calculates the ratio of the amount of food-related expenditure to the total expenditure. Moreover, if there is an item of health food / supplement in the household account book data, the amount of expenditure may be extracted, and the proportion of the cost of food / medical / medical expenses may be calculated.

  The user data classification unit 123 extracts and classifies symptom patterns related to health food from the life log data storage unit 116 and the examination data storage unit 117. For example, when the life log data is a response to a question from a user, one answer such as “I do PC work all day”, “I am stiff on my shoulders”, or “I eat a lot” Classify as “symptom pattern”. Here, the symptom pattern is a classification of a plurality of related symptoms as one pattern, or the same type of symptoms (for example, “shoulder hurts”, “shoulder shoulders”, “shoulder shoulders” etc.) 1 Say what you put together. The latter is effective for classification when the user enters life log data as text instead of asking questions. The user data classification unit 123 also classifies the extraction results of the preference extraction unit 121 and the food-related expenditure extraction unit 122 into patterns. Each classified pattern is transferred to the weighting means 131.

  The weighting means 131 weights the merit data of the health food data according to the pattern classified by the user data classification means 123, and performs matching (association) between the health food data and the user data.

  The score calculation unit 132 calculates the score of the plus element, the attention element, and the burden element based on the data associated by the weighting unit 131. That is, the merit score, alert score, and Baden score of each individual user are calculated based on the classified user data.

  The determination unit 133 compares the health score obtained by adding the merit score, the alert score, and the Baden score calculated for each health food, and determines which health food is most suitable for the user. At this time, you may make it present the cost performance which showed the merit score in order of price. Even if the cost performance is good, it is not recommended if the alert score for allergies is high. Since the Baden score varies depending on the season and region, it varies depending on the time when the healthy score is also determined. The weighting unit 131 weights each user for each score of the plus element, the attention element, and the psychological burden element, and the determination unit 133 determines the suitability using the weighting for each score. Then you may do it.

  The determination result is stored in the determination result storage unit 134. The determination result is directly output to the outside by an output means (not shown). As an output method at this time, there are methods such as output to a display device of a server, display on a screen of a user terminal, transmission to another system, storage in a portable storage medium, and printing on a printer. The determination result may be provided to a health food developer or the like and used for product development.

  The advice generation unit 135 generates advice on health food for the user based on the determination result of the determination unit 133. Specifically, it is assumed that user data such as life log data or medical examination data has been improved, and based on the improved user data, each active ingredient contained in health food is weighted, and the user data and effective data Based on the weighting for each component, the score of the plus element of the health food is calculated, and the suitability is determined based on the calculated score. By repeating such processing, it is also possible to generate a word of advice on how to improve user data such as life log data or examination data and present it to the user.

(Processing flow)
FIG. 4 is a diagram illustrating a processing flow of the healthy seafood score determination processing. In this figure, the processing order of each step may be changed as long as the relationship between the input and output of each step is not impaired.

  First, in step S01, the determination server acquires life log data and examination data. Next, in step S02, symptom patterns are extracted from the acquired life log data and examination data and classified. In step S03, the merit score of the health food that matches the symptom pattern is calculated.

  Subsequently, in step S04, the determination server determines whether the user satisfies the alert condition based on the alert data, the examination data, and the like. This is especially true when the user is pregnant or has allergic symptoms. If the alert condition is not met, the process proceeds to step S06. If the alert condition is particularly met, an alert score is calculated in step S05.

  Subsequently, in step S06, the determination server refers to the Baden data, the household account book data, and the residential area, and determines whether there is any that satisfies the Baden condition. As mentioned above, the price of the same product may vary depending on the time and region, and household expenditure may also vary monthly, so the price of the product for the current month will be included in the health food expenditure extracted from the household account book data. On the other hand, when it exceeds a predetermined ratio, the Baden condition shall be applied. If not, the process proceeds to step S08. If so, the Baden score is calculated based on household account book data, price, purchase unit, and availability in step S07.

  Subsequently, in step S08, the determination server calculates a healthy score that is the sum (comprehensive evaluation) of the merit score, the alert score, and the Baden score. In step S09, it is determined whether there is another matching health food. If there is a matching health food, the process returns to step S03 and the same process is repeated. When all the matched items are processed, the healthy food score is compared and determined in step S10, and the process is terminated.

  The functional configuration of the system has been described above, but the above-described functional configuration is merely an example, and one functional block (database and function processing unit) is divided or a plurality of functional blocks are combined into one functional block. Or may be configured as Each function processing unit reads a computer program stored in a storage device such as a ROM (Read Only Memory), flash memory, SSD (Solid State Drive), or hard disk by a CPU (Central Processing Unit) built in the device This is realized by a computer program executed by the CPU. That is, in each function processing unit, this computer program reads and writes necessary data such as a table from a database (DB; Data Base) stored in a storage device or a storage area on a memory, and may be related in some cases. This is realized by controlling hardware (for example, an input / output device, a display device, and a communication interface device). Further, the database (DB) in the embodiment of the present invention may be a commercial database, but it simply means a collection of tables and files, and the internal structure of the database itself is not questioned.

(Concrete example)
FIG. 5 is a diagram showing an example of scoring of health food related to eye strain. As shown in the figure, the user's responses extracted from the life log and medical examination data include “symptoms such as“ all-day PC work ”,“ blood circulation is poor and shoulders are stiff ”,“ meal outing is bad and meal balance is bad ”. ”, The result of weighting each component of the health food is shown in the component weighting table 200. The component weighting table 200 is indicated by “◎”, “◯”, “Δ” in descending order of effectiveness for each component, but is actually calculated numerically. In this example, “Lutein”, “Quercetin”, “Vitamin B1 / B12”, “Vitamin E” are particularly effective for this symptom.

  Comparing the weighted components of the component weighting table 200 with the component contents of the supplements A and B, calculating the score of each component, and calculating the alert score and the Baden score from other data, the entire supplement The healthy score table 201 is obtained by determining the cost performance as. For example, quercetin has a weight “◎”, but supplement A has a small content and is considered to be inferior to lutein, so the score of quercetin in supplement A is “◯ (small)”. On the other hand, since supplement B does not contain quercetin, the merit score is “x”. In Table 201, the merit score, the Allard score, the Baden score, and the comprehensive evaluation (Healthy seafood score) of the supplement are shown. In this example, supplement A is shown to have a much higher overall rating than supplement B. In Table 201, the merit score is represented as “◯ (high)”, “◯ (small)”, “×”, etc. for convenience, but “◯ (high)” indicates 5 points and “◯ (small)”. ) "May be represented by 2 points, and" x "may be represented by 0 points. The Baden score also expresses the price, purchase unit, and availability in terms of words, but it may naturally be scored. The alert score is blank in this example.

  FIG. 6 is a diagram illustrating an example of scoring of health food related to obesity. In this example, a component weighting table 210 and a healthy seafood score table 211 of users having “symptoms” such as “do not exercise”, “many eating out and poor meal balance”, and “easy to get tired” are shown. In the healthy seafood score table 211, supplements A and B are compared with health foods X and Y other than supplements. Since this user is allergic to dairy products and onions in addition to the above “symptoms”, even if the effect / price is in the order of supplement A, health food Y, supplement B, health food X The supplement B containing quercetin derived from onions and the health food Y containing lactoferrin derived from dairy ingredients have a high negative alert score, and those with a low overall health score are not recommended (for example, overall Things that have negative points).

  FIG. 7 is a diagram showing an example of a screen showing a combination of health foods. This screen shows an effective combination of health foods for users with symptoms of eye strain. In the combination 1 in the figure, only the supplement A is used, in the combination 2, the supplement B and the high lutein spinach are used, and in the combination 3, the supplement C, the high lutein spinach, and the brown rice are used. Shows the case.

  In this example, “combination 1” costs 4000 yen per month, but “combination 2” costs supplement B of 2500 yen and the price of high lutein spinach. High lutein spinach is about 300 yen higher than ordinary spinach, and depending on the season and region, if the price is about 500 yen, the total price of "Combination 2" will be 3000 yen, 1000 yen from "Combination 1" It will be cheaper. Users who originally eat spinach will only have to replace ordinary spinach with high lutein spinach, which will further reduce the burden.

  In “Combination 3”, the price of Supplement C is 1500 yen, high lutein spinach (500 yen), and brown rice prices. If the price of brown rice is about 300 yen higher than ordinary white rice, the total price will be 1500 yen + 500 yen + 300 yen = 2300 yen if white rice is changed to brown rice, about 1700 yen from "Combination 1", "Combination 2" It will be about 700 yen cheaper. By presenting a combination of health foods including cost performance in this way, advice can be provided as to what to add if there are components that are insufficient with inexpensive supplements.

  FIG. 8 is a diagram showing another example of a screen showing a combination of health foods. This screen shows a combination of effective health foods for users who are “obese”. In this example, it is assumed that “combination 2” and “combination 3” are grayed out (not recommended) because the overall evaluation is low for some reason. At this time, since the “combination 2” is cheaper than the “combination 1”, the user dares to select this, and the system “reducing the number of eating out or exercising once a week, etc. When life log data is improved, combination 2 is recommended. "Is generated and displayed. Similarly, when the user deliberately selects “Combination 3”, the system recommends “Combination 3 when the examination data is improved, such as improvement in body fat percentage, or decrease in blood pressure. Generate and display advice such as Thus, the user can be motivated to improve life log data and examination data by displaying advice including combinations of health foods that are not recommended at the present time.

(Example)
In this system, as one application example, flexible information provision to the user is possible. In other words, this system can grasp the current state of health status / symptoms from each database of accumulated user data, and can also grasp the economic situation / life lead, so even for the same symptom pattern, It is possible to propose a suitable method, that is, a method that can be continued without difficulty and with less burden.

  In addition, in this system, as another example of use, it is possible to provide information to product developers. Each database of user data accumulated in this system can be classified according to lifestyle patterns, and information on necessary products is obtained from each difference, and information is also provided for the health score determination by food developers. be able to. For example, if life records (blog, chat type AI, etc.) by smartphone / PC are stored in the database, it is also possible to acquire data such as meal contents, exercise contents, and mood changes. In addition, by using data tracking in the living / activity environment for wearables, IoT (Internet of Things) sensors, etc., it is also possible to acquire data such as the amount of activity, facial expression / feeling quantification, and work time. . From those databases, people who have good living habits such as sleeping more than 6 hours a day, resting once an hour, eating dark vegetables, and bad living habits, health It is also possible to compare with people who recommend foods, determine the shortage of health foods, request as a development monitor, and advise the developer on the results.

(Effect of embodiment)
According to this system, positive factors, caution factors, and economic burden factors are comprehensively determined for the use of health foods including supplements, and the living environment such as the user's life log, profile, residential area, and household situation is determined. In response, information on more appropriate health foods and supplements can be provided.

  In addition, a combination of supplements and health foods other than supplements is presented together with price information, and if there are nutrients that are insufficient for cheap supplements, what can be eaten additionally can be advised. Moreover, the life log acquisition means can use not only an inquiry but also various data from a physical condition data measuring device and a wearable device.

  It is also possible to analyze browsing history data on the Internet, extract user's food preferences, and use it as auxiliary data when recommending health foods. It is also possible to recommend health food that does not become a burden on the household from household account book data, or to extract the expenditure of food and the expenditure of health food to check the proportion of the expenditure of health food in the household.

  In the above embodiment, the health food containing supplements has been described. However, the present invention can be applied to other products as long as the products are weighted by user data.

  As mentioned above, although this invention was demonstrated using embodiment, it cannot be overemphasized that the technical scope of this invention is not limited to the range as described in the said embodiment. It will be apparent to those skilled in the art that various modifications or improvements can be added to the above embodiment. Further, it is apparent from the scope of the claims that the embodiments added with such changes or improvements can be included in the technical scope of the present invention. In the above embodiment, the present invention is described as a product invention, and a health tuning support system, particularly a healthy score determination server has been described. However, the present invention may also be a method invention or a computer program invention on a server. It can also be captured.

100 Healthy Seafood Score Judgment Server (Judgment Server)
DESCRIPTION OF SYMBOLS 101 Health food data acquisition means 102 Merit data storage means 103 Alert data storage means 104 Baden data storage means 110 User data acquisition means 111 Net browsing history data acquisition means 112 Life log data acquisition means 113 Examination data acquisition means 114 Household book data acquisition Means 115 Browsing history data storage means 116 Life log data storage means 117 Examination data storage means 118 Household book data storage means 121 Preference extraction means 122 Food related expenditure extraction means 123 User data classification means 131 Matching means 132 Score calculation means 133 Determination means 134 judgment result storage means 200,210 component weighting table 201,211 healthy seafood score table

Claims (7)

A determination server that determines the suitability of health food for users,
Health food data acquisition means for acquiring health food data including active ingredients, content, allergic ingredients, price, and availability of the health food;
User data acquisition means for acquiring user data including life log data which is a record of the daily life of the user and examination data in the user's medical institution;
Based on the acquired user data, weighting means for weighting each active ingredient contained in the health food,
Based on the acquired user data and the weighting for each active ingredient, the score of the positive element of the health food is calculated, the score of the attention element based on the acquired user data, and the psychological burden element Score calculating means for calculating a score;
Determining means for determining the suitability based on the calculated score;
A determination server comprising:   The determination server according to claim 1, wherein the determination unit presents a combination of a supplement and a health food other than the supplement together with the price.   The user data acquisition means includes life log data acquisition means for acquiring the life log data, the life log data acquisition means is an inquiry means for acquiring an answer to an inquiry for the user, a measurement for measuring physical condition data The determination server according to claim 1, further comprising: a wearable device that is worn by the user and records life data.   The user data acquisition unit includes a network browsing history data acquisition unit, and comprises a preference extraction unit that analyzes the acquired browsing history data and extracts a preference regarding the user's food. 4. The determination server according to any one of up to 3.   5. The user data acquisition means includes household account book data acquisition means, and comprises food related expenditure extraction means for extracting food expenditure and health food expenditure from the acquired household account book data. The determination server according to any one of the above. A method for determining the suitability of a health food for a user,
Obtaining health food data including active ingredients, content, allergic ingredients, price, and availability of the health food;
Obtaining user data including life log data that is a record of the daily life of the user and examination data at the user's medical institution;
Weighting each active ingredient contained in the health food based on the acquired user data;
Calculating a positive factor score for the health food based on the acquired user data and weighting for each active ingredient;
Calculating a score of a caution element and a score of a psychological burden element based on the acquired user data; and
Determining the suitability based on the calculated score;
A method comprising the steps of: A program for determining the suitability of health foods for users,
Obtaining health food data including active ingredients, content, allergic ingredients, price, and availability of the health food;
Obtaining user data including life log data that is a record of the daily life of the user and examination data at the user's medical institution;
Weighting each active ingredient contained in the health food based on the acquired user data; and
Calculating a positive factor score for the health food based on the acquired user data and weighting for each active ingredient;
Calculating a score of a caution element and a score of a psychological burden element based on the acquired user data; and
Determining the suitability based on the calculated score;
A program that causes a computer to execute.