Physical information evaluation device, physical information evaluation method, program, and recording medium

Abstract

To provide a body information evaluation device, a method for evaluating body information, a program, and a recording medium that can evaluate body information of a user who has consumed a consumed object.SOLUTION: A body information evaluation device 100 includes: a reception unit 111 for receiving body information of a user in relation to identification information of a consumed object; a storage unit 120 for storing, in a database, information that has been received by the reception unit 111, in which the body information of the user and the identification information of the consumed object are related to each other; and an evaluation unit 112 for calculating evaluation information of the current body of the user and evaluation information of the future body of the user when the user consumed the consumed object, on the basis of the database stored in the storage unit 120.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a physical information evaluation device, a physical information evaluation method, a program, and a recording medium. [Background technology]

[0002] Conventionally, systems for evaluating a user's physical information have been known. For example, Patent Document 1 discloses a system that estimates a user's health level by taking into account the reliability of the information, thereby improving the reliability of the estimation result. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-250583 Summary of the Invention [Problem to be solved by the invention]

[0004] However, conventional techniques still have room for improvement in evaluating the physical information of a user who has taken an ingested food.

[0005] The present invention has been made in consideration of the above circumstances, and aims to provide a physical information evaluation device, a physical information evaluation method, a program, and a recording medium that can evaluate the physical information of a user who has ingested an ingested item. [Means for solving the problem]

[0006] A physical information evaluation device according to one aspect of the present invention includes a reception unit that receives a user's physical information in association with identification information of an ingested product, a memory unit that stores the information received by the reception unit, in association with the user's physical information and the identification information of the ingested product, as a database, and an evaluation unit that calculates, based on the database stored in the memory unit, evaluation information of the user's current body and evaluation information of the user's future body when the user ingests the ingested product.

[0007] A physical information evaluation method according to one aspect of the present invention includes the steps of receiving a user's physical information in association with identification information of an ingested item, storing information in a memory unit that associates the user's physical information with the identification information of the ingested item as a database, and calculating, based on the database stored in the memory unit, current evaluation information of the user's body and future evaluation information of the user's body if the user ingests the ingested item.

[0008] A program according to one aspect of the present invention causes one or more computers to perform the following processes: accepting a user's physical information in association with identification information of an ingested item; storing information associating the user's physical information with the identification information of the ingested item as a database in a memory unit; and evaluating, based on the database stored in the memory unit, the user's current physical evaluation information and future physical evaluation information of the user if the user ingests the ingested item. [Effects of the Invention]

[0009] According to the present invention, it is possible to evaluate the physical information of a user who has taken an ingested food. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of a system for utilizing physical evaluation information. [Figure 2] FIG. 1 illustrates an example of a physical information evaluation device according to an embodiment. [Figure 3] FIG. 10 illustrates an example of a user management table. [Figure 4] FIG. 10 is a diagram illustrating an example of a physical evaluation information table. [Figure 5] FIG. 10 is a diagram illustrating an example of an intake table. [Figure 6] FIG. 10 is a diagram illustrating an example of a user preference table. [Figure 7] FIG. 10 is a diagram illustrating an example of a company information table. [Figure 8] FIG. 10 is a diagram illustrating an example of a multivariate analysis process. [Figure 9] FIG. 10 is a diagram illustrating an example of processing in the learning phase and execution phase of a learning model. [Figure 10] 10 is a sequence chart showing an example of a flow of a process executed by a physical information evaluation device in cooperation with a mobile information terminal according to an embodiment. [Figure 11] FIG. 10 is a diagram showing an example of the processing flow of a physical evaluation Web service. [Figure 12] FIG. 10 is a diagram showing an example of display of body evaluation information in the body evaluation web service. [Figure 13] FIG. 10 is a diagram showing an example of time progression of future predicted values ​​of physical evaluation information. [Figure 14] FIG. 10 is a diagram showing an example of time progression of future predicted values ​​of evaluation information of a user's body when ingestion of ingested foods and exercise are combined. [Figure 15] FIG. 10 is a diagram for explaining an example of behavioral change for a user. [Figure 16] FIG. 10 is a diagram illustrating an example of a method for proposing an exercise menu to encourage a user to change their behavior. [Figure 17] FIG. 10 is a diagram illustrating an example of a method for proposing an exercise menu to encourage a user to change their behavior. [Figure 18] FIG. 10 is a diagram showing an example of statistical data of body evaluation information provided to a manufacturer. [Figure 19] FIG. 10 is a diagram showing an example of statistical data of body evaluation information provided to a manufacturer. [Figure 20] FIG. 10 is a diagram showing an example of statistical data of body evaluation information provided to a manufacturer. DETAILED DESCRIPTION OF THE INVENTION

[0011] An embodiment of a physical information evaluation device will be described below.

[0012] FIG. 1 is a diagram illustrating an example of a system for utilizing physical evaluation information.

[0013] In this system, an image code (e.g., a QR code (registered trademark) or a barcode) is first attached to an ingested product manufactured and sold by a manufacturer. Ingestion products include, for example, confectionery, beverages, pharmaceuticals, and health foods. Health foods include, for example, foods for specified health uses, functional foods, dietary supplements, dietary supplements, fortified foods, nutritionally balanced foods, and supplements. The image code contains, for example, a product code and a URL for a website for accessing the physical evaluation web service. A user reads the image code attached to a purchased ingested product using a mobile information terminal and displays the website for the physical evaluation web service on the display screen of the mobile information terminal. The user provides the product code of the ingested product obtained from the image code along with the purchaser's physical information to the physical evaluation web service. The physical evaluation web service calculates the user's current physical evaluation information and the user's future physical evaluation information if the user consumes the ingested product. The evaluation data from the physical evaluation web service is stored in a physical evaluation information database. Statistical data on the physical evaluation information of multiple users stored in the physical evaluation information database is provided to manufacturers, for example, and used to evaluate the efficacy of ingested products.

[0014] FIG. 2 is a diagram illustrating an example of the physical information evaluation device 100. As shown in FIG.

[0015] The physical information evaluation device 100 is connected to, for example, a measurement device 200 and a mobile information terminal 300 via a communication network NW. The communication network NW is configured by, for example, a communication line, a wireless communication network, or the like.

[0016] The measurement device 200 is a device that measures the user's physical information, and includes, for example, a blood pressure monitor, a weight scale, a body composition monitor, and various wearable devices such as eyeglasses and watches. The user's physical information includes, for example, weight, body fat percentage, basal metabolic rate, average number of steps, and BMI.

[0017] The mobile information terminal 300 is a mobile information processing terminal such as a smartphone or a tablet terminal, and includes, for example, an image recognition unit 310 and a display control unit 320.

[0018] The image recognition unit 310 performs image recognition on the image code attached to the ingested item to be consumed by the user and reads the information written in the image code. The information written in the image code includes, for example, the product code of the ingested item and a URL for accessing the body evaluation web service.

[0019] The display control unit 320 displays the evaluation information of the user's body evaluated by the physical information evaluation device 100 on the display screen of the mobile information terminal 300. For example, the display control unit 320 displays the evaluation information of the user's body obtained by inputting the user's physical information into a physical evaluation web service on the display screen of the mobile information terminal 300. The evaluation information of the user's body includes, for example, an athletic age and an actual age.

[0020] The physical information evaluation device 100 includes, for example, a control unit 110 and a storage unit 120. The control unit 110 is realized by, for example, a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a GPU (Graphics Processing Unit), or may be realized by a combination of software and hardware. The program may be stored in advance in a computer-readable recording device such as a hard disk drive (HDD) or flash memory of the physical information evaluation device 100, or may be stored in a removable computer-readable recording medium such as a DVD or CD-ROM, and installed in the HDD or flash memory of the physical information evaluation device 100 by inserting the computer-readable recording medium into a drive device.

[0021] The control unit 110 includes, for example, a receiving unit 111 and an evaluation unit 112.

[0022] The receiving unit 111 receives the user's physical information in association with the product code of the ingested item. The product code of the ingested item is an example of identification information of the ingested item. The receiving unit 111 stores information in which the user's physical information is associated with the product code of the ingested item as a physical evaluation information table 122 in the storage unit 120. The physical evaluation information table 122 is an example of a data table.

[0023] The evaluation unit 112 calculates the current evaluation information of the user's body, as well as the future evaluation information of the user's body when the user ingests the ingested material, based on the body evaluation information table 122 stored in the memory unit 120.

[0024] The evaluation unit 112 inputs the user's physical information received by the reception unit 111 and predicts future evaluation information of the user's body when the user ingests the ingested food, for example, using a multivariate analysis method in which the user's physical information at multiple points in time and the product code of the ingested food are used as explanatory variables and the evaluation information is used as the objective variable.

[0025] The evaluation unit 112 may, for example, train the learning model 126 by machine learning using data that associates the user's physical information at multiple points in time with the product code and evaluation information of the ingested food as learning data, input the user's physical information received by the reception unit 111 into the learning model 126, and predict the future predicted value of the physical evaluation information when the user ingests the food.

[0026] For example, the evaluation unit 112 predicts future evaluation information of the user's body when the user consumes an ingestion for each of the user's health preference levels, and suggests an exercise menu to the user based on the predicted future evaluation information of the user's body. For example, when the user's health preference level is a first preference level, the evaluation unit 112 suggests an exercise menu to the user based on the future user's body evaluation information corresponding to the first preference level. That is, the evaluation unit 112 suggests an exercise menu to the user that is suitable for the user's health preference level. For example, when the user's health preference level is a first preference level, the evaluation unit 112 may suggest an exercise menu to the user based on the future user's body evaluation information corresponding to a second preference level that is higher than the first preference level. That is, the evaluation unit 112 may suggest an exercise menu that is more strenuous than an exercise menu that is suitable for the user's health preference level.

[0027] The evaluation unit 112 predicts future physical evaluation information of the user when the user combines ingesting ingestants and exercising, for example, based on the physical evaluation information table 122 stored in the storage unit 120. The evaluation unit 112 predicts future physical evaluation information of the user when the user combines ingesting ingestants and exercising, for example, for each user's exercise preference level, and suggests an exercise menu to the user based on the predicted future physical evaluation information of the user. That is, when the user combines ingesting ingestants and exercising, the evaluation unit 112 suggests to the user an exercise menu suitable for the user's exercise preference level. For example, when the user's exercise preference level is a first preference level, the evaluation unit 112 may suggest an exercise menu to the user based on future physical evaluation information of the user corresponding to a second preference level higher than the first preference level. That is, when the user combines ingesting ingestants and exercising, the evaluation unit 112 may suggest to the user an exercise menu with a higher load than an exercise menu suitable for the user's exercise preference level.

[0028] The storage unit 120 stores, for example, a user management table 121, a body evaluation information table 122, an intake table 123, a user preference table 124, a company information table 125, and a learning model 126.

[0029] 3 is a diagram showing an example of the user management table 121. In the user management table 121, for example, a user ID, which is identification information for identifying a user, is associated with a password, registration date, date of birth, place of residence, gender, and preference level. The password is used when the user performs user authentication for the physical evaluation Web service. The registration date indicates the date when the user information was registered in the user management table 121. The preference level indicates the user's preference level for health or exercise, and the category ID of the user preference table 124 is registered.

[0030] FIG. 4 is a diagram showing an example of the physical evaluation information table 122. In the physical evaluation information table 122, a user ID, which serves as identification information for identifying a user, is associated with a data registration date, a product ID, physical information, and physical evaluation information. The data registration date indicates the date on which the physical evaluation information was registered in the physical evaluation information table 122. The product ID indicates the identification information of an ingested product taken by the user. The physical information is information measured when the user takes the ingested product, and includes, for example, weight, body fat percentage, basal metabolic rate, average number of steps, and BMI. The physical evaluation information is evaluation information obtained by inputting the user's physical information into a physical evaluation web service, and includes, for example, athletic age and actual age. The athletic age is data that serves as an indicator of the user's athletic ability. The actual age is data that indicates the user's age. If the athletic age is lower than the actual age, it is an indicator that the user is in good health.

[0031] FIG. 5 is a diagram showing an example of the ingested item table 123. In the ingested item table 123, a company ID, which serves as identification information for identifying the manufacturer of the ingested item, is associated with a product ID, nutritional components, and ingredient category. The product ID indicates the identification information for the ingested item. The nutritional components indicate the nutritional components contained in the ingested item, and include, for example, energy, protein, lipids, carbohydrates, dietary fiber, salt, potassium, calcium, vitamin C, vitamin K, and folic acid. The ingredient category indicates the category of the ingested item based on the nutritional components of the dietary supplement ingredients.

[0032] Fig. 6 is a diagram showing an example of the user preference table 124. In the user preference table 124, the content of the user's preferences is associated with a category ID, which serves as identification information for identifying the category of the user's preferences. In the example shown in Fig. 6, the user preference table 124 has registered therein the user's degree of preference for health and the user's degree of preference for exercise, with the degree being distinguished.

[0033] 7 is a diagram showing an example of the company information table 125. In the company information table 125, a company ID, which is identification information for identifying the manufacturer of an ingested product, is associated with a company name, contact information, and address.

[0034] FIG. 8 is a diagram illustrating an example of the multivariate analysis process.

[0035] In the example shown in FIG. 8 , the attribute of the explanatory variable X in the multivariate analysis is the physical information of multiple users measured when each of them ingested one or more ingested foods, and the attribute of the response variable Y in the multivariate analysis is the physical evaluation information of the user when the user ingested one or more ingested foods. The user's physical information includes, for example, x1 (body weight), x2 (body fat percentage), x3 (basal metabolic rate), x4 (average number of steps), and x5 (BMI). The user's physical evaluation information includes, for example, y1 (exercise age) and y2 (effective age). The combinations of the explanatory variable X and the response variable Y in the multivariate analysis are managed separately for each combination of one or more ingested foods ingested by the user. In the example shown in FIG. 8 , multiple regression analysis is applied as an example of multivariate analysis, and a function indicating the correlation between the explanatory variable X and the response variable Y is calculated using, for example, the least squares method. Then, by inputting the user's physical information accepted by the accepting unit 111 into the calculated function, the user's future physical evaluation information when the user ingests the ingested foods is predicted.

[0036] FIG. 9 is a diagram showing an example of the processing of the learning phase and the execution phase of the learning model 126.

[0037] In the example shown in FIG. 9, in the learning phase, the learning model 126 is trained by machine learning using training data. The training data is, for example, data in which first data and second data are associated with each other, and is time-series data including data at multiple points in time (Dt1, Dt2, Dt3, ...). The first data includes, for example, product information and physical information. The product information is information indicating a combination of one or more ingested substances taken by each of multiple users, and includes, for example, information regarding whether or not the user ingested a given substance for a parameter set for each ingested substance. The physical information is information measured when each of multiple users ingested one or more ingested substances, and includes, for example, weight, body fat percentage, basal metabolic rate, average number of steps, and BMI. The second data includes, for example, physical evaluation information. The physical evaluation information is information calculated using a method different from that of the physical evaluation web service, and includes, for example, exercise age and actual age.

[0038] Next, in the execution phase, input data of the user to be evaluated is input to the learning model 126. The input data includes, for example, product information and physical information. The product information is information indicating a combination of one or more ingested substances taken by the user to be evaluated, and includes, for example, information regarding whether the user ingested each ingested substance for a parameter set for each ingested substance. The physical information is information measured when the user to be evaluated ingested one or more ingested substances, and includes, for example, weight, body fat percentage, basal metabolic rate, average number of steps, and BMI. The learning model 126 is implemented in a physical evaluation web service, and when input data of the user to be evaluated is input, it outputs evaluation information of the user's body. The evaluation information of the user's body includes, for example, exercise age and actual age.

[0039] FIG. 10 is a sequence chart showing an example of the flow of processing that the physical information evaluation device 100 executes in cooperation with the mobile information terminal 300.

[0040] As shown in the figure, first, the mobile information terminal 300 reads the image code attached to the ingested item (step S10). Next, the mobile information terminal 300 displays the web page of the body evaluation web service based on the URL written in the image code (step S11). Next, when a pre-registered user ID and password are input, the mobile information terminal 300 transmits the input user ID and password to the physical information evaluation device 100, thereby establishing user authentication in the body evaluation web service. Next, when the user's physical information is input, the mobile information terminal 300 associates the product code of the ingested item written in the image code with the user's physical information and transmits them to the physical information evaluation device 100.

[0041] When the physical information evaluation device 100 receives the user's physical information in association with the product code of the ingested item from the mobile information terminal 300, it updates the physical evaluation information table 122 (step S12). Next, the physical information evaluation device 100 updates the learning model 126 based on the information registered in the updated physical evaluation information table 122 (step S13). Next, the physical information evaluation device 100 analyzes the future predicted value of the physical evaluation information using the updated learning model 126 (step S14). Then, the physical information evaluation device 100 transmits the user's physical evaluation information and the future predicted value of the physical evaluation information to the mobile information terminal 300.

[0042] When the mobile information terminal 300 receives the user's physical evaluation information and the future predicted value of the physical evaluation information from the mobile information terminal 300, it suggests to the user an exercise menu to improve the user's physical evaluation information based on the received information (step S15).

[0043] FIG. 11 is a diagram illustrating an example of the processing flow of the physical evaluation Web service.

[0044] In the example shown in FIG. 11, the mobile information terminal 300 first reads the image code 400M attached to the ingested item 400 and obtains the URL of the body evaluation web service. Next, the mobile information terminal 300 displays a login screen for the body evaluation web service. Next, when a login ID and password are entered on the login screen for the body evaluation web service, the mobile information terminal 300 performs user authentication for the body evaluation web service. Next, when user authentication is successful, the mobile information terminal 300 registers the user's body information measured by the measuring device 200 in association with the product code of the ingested item written on the image code 400M.

[0045] FIG. 12 is a diagram showing an example of display of body evaluation information in the body evaluation Web service.

[0046] 12, the mobile information terminal 300 displays a first icon 300A, a second icon 300B, and a third icon 300C. In this example, the first icon 300A indicates the type of food ingested by the user as user information. The second icon 300B indicates the user's exercise age and actual age as physical evaluation information. The third icon 300C indicates the transition of the user's exercise age when the user ingests the food as a future predicted value of physical evaluation information.

[0047] FIG. 13 is a diagram showing an example of time transition of future predicted values ​​of physical evaluation information.

[0048] The example shown in Figure 13 shows the time progression of future predicted values ​​of body evaluation information for each user's health preference level. In this example, the future predicted values ​​of body evaluation information tend to gradually decrease over time, regardless of the user's health preference level. In other words, this shows that if the user continues to ingest ingested substances, the user's body evaluation information will gradually improve. Furthermore, in this example, the higher the user's health preference level, the greater the future predicted values ​​of body evaluation information tend to decrease over time. In other words, this shows that when the user's health preference level is high, the user tends to actively ingest ingested substances, and the user's body evaluation information will improve significantly.

[0049] FIG. 14 is a diagram showing an example of the time transition of the future predicted value of the evaluation information of the user's body when taking in food and exercising in combination.

[0050] The example shown in Figure 14 shows the time progression of future predicted values ​​of body evaluation information for each user's exercise preference level. In this example, the user's exercise preference level is classified into two levels: "no exercise habit" and "exercise habit," and the time progression of future predicted values ​​of body evaluation information for each user's health preference level in each category is shown. In this example, when a user falls into the "exercise habit" category, the future predicted values ​​of body evaluation information tend to decrease more significantly over time than when the user falls into the "no exercise habit" category. In other words, this shows that when a user's exercise preference level is high, the combined effect of ingesting and exercising tends to be greater.

[0051] FIG. 15 is a diagram for explaining an example of behavioral change for a user.

[0052] In the example shown in Figure 15, the user's health preference level corresponds to "passive efforts," and the user is encouraged to change his / her behavior to change his / her health preference level to "normal, casual efforts." Also, in this example, the user's exercise preference level corresponds to "no exercise habit," and the user is encouraged to change his / her behavior to change his / her exercise preference level to "exercise habit."

[0053] FIG. 16 is a diagram for explaining an example of a method for proposing an exercise menu for encouraging a user to change their behavior when taking ingestion products and exercising in combination.

[0054] The example shown in FIG. 16 shows future predicted values ​​of physical evaluation information for each user's health preference level. In this example, the user's health preference level corresponds to "passive effort." An exercise menu with a relatively low load is proposed based on the difference between the future predicted value of physical evaluation information corresponding to the "passive effort" preference level and the current physical evaluation value. That is, when the user's health preference level is the first preference level, an exercise menu is proposed to the user based on the future user's physical evaluation information corresponding to the first preference level. In this case, an exercise menu appropriate for the user's health preference level is proposed to the user. Furthermore, an exercise menu with a relatively high load is proposed based on the difference between the future predicted value of physical evaluation information corresponding to the "normal, casual effort" preference level and the current physical evaluation value. That is, when the user's health preference level is the first preference level, an exercise menu is proposed to the user based on the future user's physical evaluation information corresponding to the second preference level, which indicates a higher health preference level than the first preference level. In this case, an exercise menu that encourages the user to improve their level of interest in health is proposed to the user.

[0055] FIG. 17 is a diagram for explaining an example of a method for proposing an exercise menu for encouraging a user to change their behavior when taking ingestion products and exercising in combination.

[0056] In the example shown in FIG. 17, the user's exercise preference level is classified into two levels: "no exercise habit" and "exercise habit," and the graph shows the time transition of the future predicted value of the body evaluation information for each user's health preference level in each category. In this example, the user's exercise preference level corresponds to "no exercise habit." An exercise menu with a relatively low load is proposed based on the difference between the future predicted value of the body evaluation information corresponding to the preference level of "no exercise habit" and the current body evaluation value. In other words, when the user's exercise preference level is a first preference level, an exercise menu is proposed to the user based on the user's future body evaluation information corresponding to the first preference level. In this case, an exercise menu appropriate for the user's exercise preference level is proposed to the user. Furthermore, an exercise menu with a relatively high load is proposed based on the difference between the future predicted value of the body evaluation information corresponding to the preference level of "exercise habit" and the current body evaluation value. That is, when the user's exercise preference level is defined as a first preference level, an exercise menu is proposed to the user based on the future user's physical evaluation information corresponding to a second preference level, which indicates a higher preference level for the user's health than the first preference level. In this case, an exercise menu that encourages the user to improve their exercise preference level is proposed to the user.

[0057] FIG. 18 is a diagram showing an example of statistical data of body evaluation information provided to manufacturers.

[0058] The example shown in Figure 18 shows statistical values ​​of future predicted values ​​of physical evaluation information for each ingredient category of ingested foods. The statistical values ​​include, for example, the average and median. In this example, the future predicted value of physical evaluation information corresponding to ingredient category 2 of ingested foods has decreased significantly over time compared to the future predicted value of physical evaluation information corresponding to ingredient category 1 of ingested foods. In other words, this shows that ingredient category 2 of ingested foods contributes significantly to the efficacy of ingested foods compared to ingredient category 1 of ingested foods.

[0059] FIG. 19 is a diagram showing an example of statistical data of body evaluation information provided to manufacturers.

[0060] The example shown in Figure 19 shows statistical values ​​of future predicted values ​​of physical evaluation information for each ingredient category of ingested foods, categorized based on the user's age. In this example, the future predicted values ​​of physical evaluation information for users aged 40 or older decrease significantly over time compared to the future predicted values ​​of physical evaluation information for users under 40. In other words, this shows that when a user aged 40 or older ingests an ingested food, the efficacy of the ingested food is greater than when a user under 40 ingests the food.

[0061] FIG. 20 is a diagram showing an example of statistical data of body evaluation information provided to manufacturers.

[0062] The example shown in Figure 20 shows the amount of change in the body evaluation information for each ingested item. This example shows the amount of change in the user's body evaluation information when ingesting ingested item A or ingested item B between two points, time t0 and time t1. For example, the amount of change in the body evaluation information for each user may be displayed as a list, or statistics of the amount of change in the body evaluation information for multiple users may be displayed. In this example, the amount of change in the body evaluation information corresponding to ingested item A tends to be greater than the amount of change in the body evaluation information corresponding to ingested item B. This shows that ingested item A has greater health benefits than ingested item B.

[0063] According to the above embodiment, the following effects can be obtained.

[0064] (1) The physical information evaluation device 100 calculates the current evaluation information of the user's body and the future evaluation information of the user's body if the user ingests the ingested food based on a database that associates the user's physical information with the product code of the ingested food. This allows the physical information of the user who ingests the ingested food to be evaluated with a high degree of flexibility.

[0065] (2) The physical information evaluation device 100 inputs the user's physical information received by the receiving unit 111 and predicts future physical evaluation information of the user when the user ingests the ingested food, using a multivariate analysis method with the user's physical information at multiple points in time and the product code of the ingested food as explanatory variables and the user's physical evaluation information as a response variable. This makes it possible to calculate with high reliability the future physical evaluation information of the user when the user ingests the ingested food.

[0066] (3) The physical information evaluation device 100 inputs the user's physical information received by the receiving unit 111 into a learning model 126 that has been trained by machine learning using data that associates the user's physical information at multiple points in time with the product code and evaluation information of ingested foods as learning data, and predicts future evaluation information of the user's body when the user ingests the ingested foods. This makes it possible to calculate with high reliability the evaluation information of the user's body when the user ingests the ingested foods.

[0067] (4) The physical information evaluation device 100 predicts future evaluation information of a user's body when the user combines ingestion of an ingested food with exercise, based on a database that associates the user's physical information with the product code of the ingested food. This allows for an even greater degree of freedom in evaluating the physical information of a user who has ingested an ingested food.

[0068] (5) The physical information evaluation device 100 predicts the user's future physical evaluation information when the user combines ingestion of ingested foods and exercise for each level of the user's health preferences, and proposes an exercise menu to the user based on the predicted future physical evaluation information of the user. This makes it possible to propose an exercise menu taking the user's health preferences into consideration.

[0069] (6) When the user's health preference level is the first preference level, the physical information evaluation device 100 proposes an exercise menu to the user based on the future user's physical evaluation information corresponding to the first preference level. This makes it possible to propose an exercise menu suited to the user's health preference.

[0070] (7) When the user's health preference level is a first preference level, the physical information evaluation device 100 proposes an exercise menu to the user based on the future user's physical evaluation information corresponding to a second preference level higher than the first preference level. This makes it possible to propose an exercise menu in a manner that changes the user's health preference level.

[0071] (8) The physical information evaluation device 100 predicts future physical evaluation information of the user when the user combines ingestion of ingested substances and exercise for each level of preference for exercise, and proposes an exercise menu to the user based on the predicted future physical evaluation information of the user. This makes it possible to propose an exercise menu taking into account the user's health preferences.

[0072] (9) When the user's exercise preference level is a first preference level, the physical information evaluation device 100 proposes an exercise menu to the user based on the future evaluation information of the user's body that corresponds to the first preference level. This makes it possible to propose an exercise menu that suits the user's exercise preference.

[0073] (10) When the user's exercise preference level is a first preference level, the physical information evaluation device 100 proposes an exercise menu to the user based on the future user's physical evaluation information corresponding to a second preference level that is higher than the first preference level. This makes it possible to propose an exercise menu in a manner that changes the user's exercise preference.

[0074] The above embodiment can also be implemented in the following manner.

[0075] In the above embodiment, taking into consideration the user's preference for exercise, restrictions may be placed on the method of proposing an exercise menu to the user, for example, by setting an upper limit on the load or the exercise time.

[0076] In the above embodiment, taking into consideration the user's level of health preference, restrictions may be placed on the method of proposing an exercise menu to the user, for example, by setting an upper limit on the load or the exercise time.

[0077] In the above embodiment, the information suggested to the user in consideration of the user's level of health preference is not limited to an exercise menu, and may also include, for example, a method for suggesting to the user how to take in ingested foods.

[0078] The above-described embodiments are intended to facilitate understanding of the present invention and are not intended to limit the scope of the present invention. The present invention may be modified or improved without departing from its spirit, and equivalents are also encompassed within the scope of the present invention. In other words, designs modified by those skilled in the art as appropriate are also encompassed within the scope of the present invention as long as they incorporate the characteristics of the present invention. For example, the elements and their arrangements, materials, conditions, shapes, sizes, etc., included in the embodiments are not limited to those illustrated and can be modified as appropriate. Furthermore, the embodiments are merely examples, and partial substitutions or combinations of the configurations shown in different embodiments are naturally possible. These are also encompassed within the scope of the present invention as long as they incorporate the characteristics of the present invention. [Explanation of symbols]

[0079] 100...physical information evaluation device, 110...control unit, 111...reception unit, 112...evaluation unit, 120...memory unit, 121...user management table, 122...physical evaluation information table, 123...ingestion table, 124...user preference table, 125...company information table, 126...learning model, 200...measuring device, 300...mobile information terminal, 310...image recognition unit, 320...display control unit, NW...communication network.

Claims

1. a receiving unit that receives the user's physical information in association with identification information of an ingested item, the identification information being associated with information on the manufacturer of the ingested item; a storage unit that stores, as a database, information in which the physical information and the identification information are associated with each other and the user's health preference level, which information is received by the receiving unit; an evaluation unit that calculates, based on the database stored in the storage unit, evaluation information on the current user's body and evaluation information on the future user's body based on the user's level of preference for health when the user ingests an ingestion item to which the identification information is assigned; a display unit that displays a behavioral modification suggestion for the user based on at least the evaluation information of the future user's body; a providing unit that provides the manufacturer with evaluation information on the future user's body in order to evaluate the efficacy of the ingested product; Equipped with Physical information assessment device.

2. The evaluation unit inputs the user's physical information received by the reception unit and predicts future physical evaluation information of the user when the user ingests the ingested food to which the identification information has been assigned, using a multivariate analysis method with the user's physical information at multiple time points and the identification information of the ingested food stored as the database in the storage unit as explanatory variables and the user's physical evaluation information as a target variable. The physical information evaluation device according to claim 1 .

3. The evaluation unit inputs the user's physical information received by the reception unit into a learning model trained by machine learning using data stored as the database in the storage unit, which data associates the user's physical information at multiple points in time with the identification information and evaluation information of the ingested food, and predicts future evaluation information of the user's body when the user ingests the ingested food to which the identification information has been assigned. The physical information evaluation device according to claim 1 .

4. The storage unit further stores the user's exercise preference degree as a database, The degree of preference for exercise includes two classifications: whether or not one exercises regularly; the evaluation unit predicts future evaluation information of the user's body when the user takes the food item to which the identification information is assigned and exercises habitually in combination, based on the database stored in the storage unit; The physical information evaluation device according to claim 1 .

5. The evaluation unit predicts future physical evaluation information of the user when the intake of the foodstuff to which the identification information is assigned is combined with the habitual exercise for each level of the user's health preference, and suggests to the user an exercise menu having a load determined based on the difference between the predicted future physical evaluation information of the user and the current physical evaluation information of the user. The physical information evaluation device according to claim 4 .

6. the evaluation unit, when the user's health preference level is a first preference level, suggests an exercise menu to the user based on evaluation information of the user's future body corresponding to the first preference level; The physical information evaluation device according to claim 5 .

7. a reception unit that receives the user's physical information in association with identification information of the ingested item; a storage unit that stores, as a database, information that associates the physical information with the identification information received by the receiving unit and the user's health and exercise preference level; an evaluation unit that calculates, based on the database stored in the storage unit, evaluation information on the current user's body and evaluation information on the user's future body when the user ingests the ingested food to which the identification information is assigned; Equipped with The degree of preference for exercise includes two classifications: whether or not one exercises regularly; The evaluation unit predicting future evaluation information of the user's body when the user takes the food to which the identification information is assigned and exercises habitually in combination for each level of the user's health preference; a means for proposing to the user an exercise menu having a load determined based on a difference between the future user's physical evaluation information corresponding to a second preference level, the second preference level being higher than the first preference level, and the current user's physical evaluation information, where the user's health preference level is a first preference level; Including, Physical information assessment device.

8. a reception unit that receives the user's physical information in association with identification information of the ingested item; a storage unit that stores, as a database, information that associates the physical information with the identification information received by the receiving unit and the user's health and exercise preference level; an evaluation unit that calculates, based on the database stored in the storage unit, evaluation information on the current user's body and evaluation information on the user's future body when the user ingests the ingested food to which the identification information is assigned; Equipped with The degree of preference for exercise includes two classifications: whether or not one exercises regularly; The evaluation unit a means for inputting the user's physical information received by the receiving unit into a learning model trained by machine learning using data stored as the database in the storage unit, which data associates the user's physical information at multiple points in time with the identification information and evaluation information of an ingested product as learning data, and predicting future evaluation information of the user's physical condition when the user ingests the ingested product to which the identification information has been assigned; a means for predicting future physical evaluation information of the user when the user takes in an ingestion for each level of preference for exercise of the user, and when the user's level of preference for exercise is no habitual exercise, proposing to the user an exercise menu having a load determined based on the difference between the future user's physical evaluation information corresponding to the preference level of no habitual exercise and the current user's physical evaluation information, and an exercise menu having a load determined based on the difference between the future user's physical evaluation information corresponding to the preference level of habitual exercise and the current user's physical evaluation information; Including, Physical information assessment device.

9. receiving the user's physical information in association with identification information of the ingested item, the identification information being associated with information on the manufacturer of the ingested item; storing information associating the user's physical information with the identification information of the ingested items and the user's health preference level as a database in a storage unit; calculating, based on the database stored in the storage unit, evaluation information on the current user's body and evaluation information on the future user's body based on the user's level of preference for health when the user ingests the ingestion product to which the identification information is assigned; displaying, on a display unit, a suggestion for behavioral modification to the user based on at least the evaluation information of the future user's body; providing the manufacturer with evaluation information of the future user's body to evaluate the efficacy of the ingestion product; Including, Physical information assessment method.

10. On one or more computers, A process of accepting the user's physical information in association with identification information of an ingested item, the identification information being associated with information on the manufacturer of the ingested item; A process of storing information associating the user's physical information with the identification information of the ingested items and the user's health preference level as a database in a storage unit; a process of evaluating, based on the database stored in the storage unit, the current user's physical evaluation information and the future user's physical evaluation information based on the user's health preference level when the user ingests the ingestion product to which the identification information is assigned; a process of displaying a behavioral modification suggestion to the user on a display unit based on at least the evaluation information of the future user's body; providing the manufacturer with evaluation information of the future user's body in order to evaluate the efficacy of the ingestion product; Execute program.

11. A computer-readable recording medium storing the program according to claim 10.

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