Taste state estimation method, food and drink recommendation method, device, and program

Abstract

To provide an improved method, device and program for estimating the taste condition of a person in consideration of variations in the sense of taste and smell of the person.SOLUTION: A taste condition estimation method is provided, comprising acquiring a health evaluation value 21 related to the health condition of a user 98, and evaluating the taste condition 25 of the user 98 based on an estimation model 24 including a relationship between health evaluation values and taste-related sensory evaluation values of a human population and the health evaluation value 21.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a method for estimating a user's taste state, and a method, device, and program for suggesting food and drink according to the estimated taste state. [Background technology]

[0002] The role of meals is not limited to simply ingesting food or obtaining nutrition. The act of eating brings about a sense of satisfaction, such as deliciousness or enjoyment, and enhances mental health. Increasing meal satisfaction is an important factor for maintaining and improving quality of life. Various efforts have been made to increase meal satisfaction. For example, Patent Document 1 below discloses a method and system for proposing an optimal menu tailored to the physical condition of each individual. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2004-054365 A Summary of the Invention [Problem to be solved by the invention]

[0004] Human taste sensitivity and the desire for each taste (preference) are also affected by the person's physical condition and the time of day. For example, even if the same person ingests the same food or drink, depending on the person's physical condition and the time of day, the food or drink may taste saltier than usual and taste less delicious. Such fluctuations in human taste and smell are often discussed among people in companies and research institutes who conduct sensory evaluations of food and drink.

[0005] Patent Document 1 proposes an optimal menu according to the physical condition of each individual (gender, height, weight, age, chronic illness, and lifestyle issues). However, Patent Document 1 does not provide any specific measures for the fluctuation of human taste and smell. In order to provide delicious food and drink with high satisfaction in meals, it is required to estimate the state of human taste taking into account the fluctuation of human taste and smell.

[0006] An object of the present invention is to provide an improved method, device, and program for estimating a human taste state taking into account fluctuations in the human sense of taste and smell. [Means for solving the problem]

[0007] The present invention for solving the above problems includes, for example, the following aspects.

[0008] (Section 1) acquiring a health evaluation value relating to a health condition of a user; estimating a taste state of the user based on an estimation model including a correlation between a health evaluation value and a sensory evaluation value related to taste in a human population and the health evaluation value; A taste state estimation method comprising: (Section 2) Item 2. The method according to item 1, wherein the taste state includes information on at least one selected from the group consisting of taste intensity, taste preference, taste aftertaste, taste detection ability, taste recognition ability, and taste evaluation. (Section 3) Item 3. The method according to item 1 or 2, wherein the health condition includes at least one selected from the group consisting of fatigue, insomnia, and physical and mental health conditions. (Section 4) The estimation model is A first correlation representing a correlation between the insomnia score and a sensory evaluation value regarding a taste aftertaste; A second correlation representing a correlation between the insomnia score and the sensory evaluation value regarding taste preference; A third correlation represents a correlation between the insomnia score and the sensory evaluation value regarding the taste evaluation of the food. The method according to any one of items 1 to 3, comprising at least one of the following: (Section 5) The method further includes the step of obtaining information regarding a time period of use; The estimation model further includes a correlation between the circadian rhythm of taste in a human population and a sensory evaluation value related to taste, 5. The method according to any one of claims 1 to 4, wherein the step of estimating the taste state estimates the user's taste state further based on information relating to the usage time period. (Section 6) The estimation model is A fourth correlation represents the correlation between the circadian rhythm of taste and the sensory evaluation value of taste intensity; The fifth correlation represents the correlation between the circadian rhythm of taste and the sensory evaluation score on taste recognition ability; Item 6. The method according to item 5, comprising at least one of the following: (Section 7) Item 5. The method according to any one of items 1 to 4, wherein the estimation model includes a correlation between the circadian rhythm of taste, a health evaluation value, and a sensory evaluation value related to taste in a human population. (Section 8) Each step of a taste state estimation method according to any one of items 1 to 7 for estimating a taste state of a user; presenting information about food and drink according to the user's taste state based on the estimated taste state; The food and beverage suggestion method includes: (Section 9) Item 9. The method according to item 8, wherein the information about the food or beverage includes at least one selected from the group consisting of the name, image, price, place of origin, variety, nutritional components, and recipe information of the food or beverage. (Section 10) The method according to item 8 or 9, wherein the step of presenting information about food and beverages comprises comparing the estimated taste state with a food and beverage database in which information about food and beverages is stored, thereby presenting information about food and beverages according to the user's taste state. (Section 11) The method according to any one of clauses 8 to 10, wherein the step of presenting information about the food and beverages is based on information fed back from a person who has used the presented information about the food and beverages, and information about the food and beverages corresponding to the user's taste state is presented based on the information fed back regarding the taste evaluation or satisfaction level for the food and beverages and the estimated taste state. (Section 12) Item 12. The method according to any one of items 8 to 11, wherein the food or drink is an agricultural product. (Section 13) a health evaluation value acquiring means for acquiring a health evaluation value related to a health state of a user; a taste state estimation means for estimating a taste state of the user based on an estimation model including a correlation between a health evaluation value and a sensory evaluation value related to taste in a human group and the health evaluation value; A taste state estimation device comprising: (Section 14) Each means of the taste state estimation device according to item 13 for estimating a taste state of a user; a means for presenting information about food and drink according to the user's gustatory state based on the estimated gustatory state; A food and beverage recommendation device comprising: (Section 15) 13. A program for causing a computer to execute each step of the method according to any one of items 1 to 12. (Section A) Item 13. The method according to any one of items 3 to 12, wherein the fatigue includes physical fatigue and mental fatigue as factors. (Section B) The method according to any one of items 3 to 12, wherein the mental and physical health conditions include factors such as physical symptoms, anxiety and insomnia, social activity disorders and depression tendencies. (Section C) Item 13. The method according to any one of items 1 to 12, wherein the taste includes at least one selected from the group consisting of sweetness, saltiness, sourness, bitterness, and umami. Effect of the Invention

[0009] According to the present invention, it is possible to provide an improved method, device and program for estimating a human taste state by taking into account fluctuations in the human sense of taste and smell. [Brief description of the drawings]

[0010] [Figure 1] FIG. 2 is a diagram showing a usage mode of the gustatory state estimating device according to one embodiment of the present invention, illustrating a usage mode when estimating a gustatory state. [Diagram 2] FIG. 1 is a diagram illustrating a usage mode of a taste state estimating device according to one embodiment of the present invention, and is a diagram for explaining a usage mode when conducting a taste test for creating an estimation model. [Diagram 3] 1 is a block diagram for explaining functions of a gustatory state estimating device according to an embodiment of the present invention. FIG. [Figure 4] 1 is a flowchart illustrating a taste state estimating method according to an embodiment of the present invention. [Diagram 5] FIG. 2 is a schematic diagram for explaining the flow of data processing in the taste state estimating device according to one embodiment of the present invention, in the case where information relating to food and drink is handled. [Figure 6] 1 is a schematic diagram for explaining the flow of data processing in a taste state estimating device according to one embodiment of the present invention, and is a diagram for the case where information relating to agricultural products is handled as information relating to food and beverages. FIG. [Figure 7] 6 is an example of data display or data input in the taste state estimating device shown in FIG. 5. [Figure 8] FIG. 2 is a diagram showing the concentrations of aqueous solutions used for each taste in the taste test in Example 1. [Figure 9] 1 is a graph showing the results of the taste test in Example 1, and illustrating the results regarding the circadian rhythm of taste. (A) shows the evaluation value of the taste intensity for a sweet aqueous solution. (B) shows the evaluation value of the taste intensity for a bitter aqueous solution. [Figure 10]1 is a graph showing the results of the taste test in Example 1, and illustrating the results regarding the circadian rhythm of taste. (A) shows the perception threshold (the lowest concentration that could be recognized as bitter) and the acceptable concentration for bitterness. (B) shows the perception threshold (the lowest concentration that could be recognized as umami) and the preferred concentration for umami. [Figure 11] 1 shows the results of the taste test in Example 1, and is a graph for explaining the results regarding taste and poor physical condition. (A) shows the change in aftertaste for sweetness for the healthy group and the insomnia group. (B) shows the change in aftertaste for umami for the healthy group and the insomnia group. (C) shows the change in aftertaste for sourness for the healthy group and the insomnia group. [Figure 12] 1 is a graph showing the results of the taste test in Example 1, illustrating the results relating to taste and poor physical condition. The preferred concentration of sweetness is shown for a healthy group and an insomnia group. [Figure 13] 1 is a graph showing the results of the taste test in Example 1, and is intended to explain the results relating to taste and poor physical condition. (A) shows the taste evaluation scores of bitter chocolate for the healthy group and the insomnia group. (B) shows the taste evaluation scores of dry sausage for the healthy group and the insomnia group. [Figure 14] 1 shows the results of the taste test in Example 1, and is an example of a model showing the influence (large influence) of the evaluator's state on taste and taste preference. [Figure 15] 1 shows the results of the taste test in Example 1, and is an example of a model showing the influence (moderate) of the evaluator's condition on taste and taste preference. [Figure 16] 1 shows the results of the taste test in Example 1, and is an example of a model showing the influence (small influence) of the evaluator's state on taste and taste preference. [Figure 17] 1 shows the results of the taste test in Example 1, and is an example of a sensory evaluation model showing the influence of environmental factors such as evaluation time and room temperature, and poor physical condition such as insomnia on taste evaluation. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In the following description and drawings, the same reference numerals denote the same or similar components, and therefore, redundant description of the same or similar components will be omitted.

[0012] [Apparatus and Method Overview] Fig. 1 and Fig. 2 are diagrams for explaining a usage mode of a gustatory state estimating device according to an embodiment of the present invention. Fig. 1 shows a usage mode when estimating a gustatory state, and Fig. 2 shows a usage mode when conducting a taste test for creating an estimation model. The taste test shown in Fig. 2 is conducted in advance before estimating the gustatory state shown in Fig. 1.

[0013] -Estimation of taste state and presentation of food and drink Please refer to FIG. 1. A taste state estimation device 100 (hereinafter, also simply referred to as device 100) according to an embodiment is a device that estimates a taste state of a user 98 (e.g., information on taste intensity, taste preference, taste aftertaste, taste detection ability, taste recognition ability, and food taste evaluation) based on a score (hereinafter, also referred to as health evaluation value) on the health state of the user 98 (e.g., fatigue, insomnia, and mental and physical health state) and an estimation model 24. The estimation model 24 is an association in a human population, and includes an association between a health evaluation value and a sensory evaluation value on taste. The device 100 further presents information on food and drink according to the taste state of the user 98 (e.g., recommended menus and recipes for those menus) based on the estimated taste state.

[0014] A person's taste sensitivity and desire (preference) for each taste are affected by the person's physical condition and time of day. In one embodiment of the present invention, the taste state of the user 98 is estimated from the health state of the user 98 based on an estimation model including the correlation between a health evaluation value and a sensory evaluation value related to taste in a human group. In this way, the taste state of the user 98 is estimated taking into account the fluctuations in the user's sense of taste and smell.

[0015] The procedure will be described below. The user 98 answers questions about health evaluation, which are displayed on, for example, the display unit 32 of the device 100, to input a score (health evaluation value) about his / her own health condition into the device 100. In this embodiment, the questions about health evaluation are a questionnaire about fatigue. The questionnaire about fatigue includes, for example, a simple question such as "Are you tired and would like to rest?" In another embodiment, the questions about health evaluation are, for example, three types, such as the Chalder Fatigue Scale, the Athens Sleep Scale, and the General Health Questionnaire.

[0016] The device 100 stores an estimation model 24 including a correlation between a health evaluation value and a sensory evaluation value related to taste in a human population. The estimation model 24 may include a plurality of correlations. Such correlations between health evaluation values ​​and sensory evaluation values ​​related to taste stored in the estimation model 24 are generated in advance by a taste test in a human population, which will be described later with reference to FIG. 2.

[0017] The device 100 estimates the taste state of the user 98 based on the acquired health evaluation value of the user 98 and the estimation model 24. The device 100 further presents information on food and drink according to the taste state of the user 98 (e.g., recommended menus) based on the estimated taste state. The estimated taste state and the information on food and drink according to the taste state are displayed on, for example, the display unit 32 of the device 100.

[0018] Furthermore, in this embodiment, the user 98 inputs time information (for example, time divisions of morning (8:00), afternoon (12:00), and evening (19:00) as time period information) in response to the questions regarding health evaluation to the device 100. The device 100 estimates the taste state of the user 98 based on the acquired time information of the user 98. In this case, the estimation model 24 further includes the association between the circadian rhythm of taste in a human population and a sensory evaluation value related to taste. The circadian rhythm of taste is a daily rhythm in which subjective taste sensitivity and preferences change throughout the day.

[0019] - Conduct taste tests to create estimation models Please refer to Fig. 2. The estimation model 24 used by the device 100 to estimate the taste state includes a correlation between a health evaluation value and a sensory evaluation value related to taste in a human population. Such a correlation included in the estimation model 24 is generated in advance by performing a plurality of types of taste tests in advance for a plurality of types of food and drink 199 by a plurality of evaluators 198 as taste tests in a human population.

[0020] The evaluator 198 performs a sensory evaluation of taste for each of a plurality of types of food and drink 199, and inputs the sensory evaluation value for taste into the device 100. The taste tests include, for example, a test on taste intensity, a test on taste preference, a test on taste aftertaste, a test on taste detection ability and taste recognition ability (cognitive threshold), and a taste evaluation. The sensory evaluation for taste is performed for each of the five tastes, for example, sweetness, saltiness, sourness, bitterness, and umami.

[0021] The evaluator 198 answers questions about health evaluation displayed on, for example, the display unit 32 of the device 100, thereby inputting a health evaluation value about his / her own health condition (for example, fatigue, insomnia, and mental and physical health condition) into the device 100. In this embodiment, the questions about health evaluation are a questionnaire about fatigue. In another embodiment, the questions about health evaluation are, for example, three types of questions, namely, the Chalder Fatigue Scale, the Athens Sleep Scale, and the General Health Questionnaire. The estimation model creation unit 14 provided in the device 100 creates an association between the health evaluation value and the sensory evaluation value about taste in a human group based on the sensory evaluation values ​​about taste and the health evaluation values ​​obtained from the multiple evaluators 198, and creates an estimation model 24 including the created association.

[0022] In the taste test, the evaluator 198 can input time information when the sensory evaluation of the food or drink 199 was performed to the device 100. The estimation model creation unit 14 can further create a correlation between the circadian rhythm of taste in a human group and the sensory evaluation value related to taste based on the time information when the sensory evaluation was performed by the evaluator 198, which is obtained from the multiple evaluators 198, and can include the correlation in the estimation model 24.

[0023] [Device configuration] FIG. 3 is a block diagram for explaining functions of the gustatory state estimating device according to one embodiment of the present invention.

[0024] The gustatory state estimation device 100 according to an embodiment includes a data processing unit 10, an auxiliary storage device 20, an input unit 31, a display unit 32, and a communication interface unit (communication I / F unit) 33. The data processing unit 10 is configured as software, and the auxiliary storage device 20, the input unit 31, the display unit 32, and the communication I / F unit 33 are configured as hardware. The gustatory state estimation device 100 can be configured using, for example, a general-purpose computer such as a personal computer, a tablet terminal, a smartphone, or the like. Although not shown in the figure, the gustatory state estimation device 100 further includes, as hardware configuration, a processor such as a CPU that processes data, and a memory that the processor uses as a working area for data processing.

[0025] The data processing unit 10 is a functional block that is realized by a processor executing a taste state estimation program 29 (hereinafter, also simply referred to as the program 29), which will be described later. In this embodiment, the data processing unit 10 is provided as a software functional block.

[0026] The health evaluation value acquisition unit 11 acquires health evaluation value data 21 relating to the health condition of the user 98. The time information acquisition unit 12 acquires time information data 22 at which the user 98 responded to the health evaluation. The health evaluation value data 21 and time information data 22 are acquired, for example, via the input unit 31 and the communication I / F unit 33, and stored in the auxiliary storage device 20.

[0027] In this embodiment, the user 98 inputs the health evaluation value data 21 via a dialog box 81 displayed on the display unit 32 of the device 100, as shown in Fig. 1. In this embodiment, the time information data 22 is acquired from a clock function of an operating system (OS) included in the device 100.

[0028] The sensory evaluation value acquisition unit 13 and the estimation model creation unit 14 function when a taste test is performed in a human population. The taste test is performed in advance before estimating the taste state. The sensory evaluation value acquisition unit 13 acquires data 23 of sensory evaluation values ​​related to taste by a plurality of evaluators 198. The sensory evaluation value data 23 is acquired, for example, via the input unit 31 or the communication I / F unit 33, and stored in the auxiliary storage device 20. The estimation model creation unit 14 generates an association between the health evaluation value and the sensory evaluation value related to taste in the human population based on the sensory evaluation values ​​and health evaluation values ​​related to taste acquired from the plurality of evaluators 198, and creates an estimation model 24 including the generated association. The estimation model creation unit 14 further creates an association between the circadian rhythm of taste in the human population and the sensory evaluation value related to taste based on time information acquired from the plurality of evaluators 198 at which the sensory evaluation was performed by the evaluators 198, and can include the association in the estimation model 24. The created estimation model 24 is stored in the auxiliary storage device 20.

[0029] In this embodiment, the sensory evaluation value and the health evaluation value are input to the device 100 by the evaluator 198 during the taste test, as exemplified in FIG. 2, through dialog boxes 71 to 75 displayed on the display unit 32 of the device 100. The dialog boxes 71 to 74 are dialog boxes for the evaluator 198 to input the sensory evaluation value, and are, in order, a dialog box for a test on taste intensity, a test on taste preference, a test on taste aftertaste, and a taste evaluation. The dialog box 75 is a dialog box for the evaluator 198 to input the health evaluation value during the taste test. In this embodiment, the time information at which the sensory evaluation is performed by the evaluator 198 during the taste test is acquired from a clock function of an operating system (OS) provided in the device 100.

[0030] The taste state estimation unit 15 estimates the taste state of the user 98 based on the estimation model 24 and the health evaluation value data 21 of the user 98. Estimated taste state data 25 is stored in the auxiliary storage device 20. In this embodiment, the estimated taste state data 25 is displayed via a dialog box 82 on the display unit 32 of the device 100, as exemplified in FIG.

[0031] The food and drink information presentation unit 16 presents information about food and drink according to the taste state of the user 98 based on the estimated taste state data 25. In this embodiment, the food and drink information presentation unit 16 presents information about food and drink according to the taste state of the user 98 by comparing the estimated taste state data 25 with a food and drink database 26 in which information about food and drink is stored. The information about food and drink includes, for example, recommended menus and recipes for those menus. In this embodiment, the information about food and drink according to the taste state of the user 98 is displayed on the display unit 32 of the device 100 via a dialog box 83, as exemplified in FIG. 1.

[0032] Furthermore, the food and beverage information presentation unit 16 can present information about food and beverages according to the taste state of the user 98 by collating the user data 27, the estimated taste state data 25, and the food and beverage database 26. The food and beverage database 26 can include information about, for example, the nutritional components of the food and beverages, and the user data 27 can include, for example, information about the food preferences of the user 98 (for example, low-salt mode, low-sugar mode, liking strong flavors, etc.) and information about the lifestyle of the user 98. The food and beverage database 26 and the user data 27 will be described in detail later.

[0033] When the user data 27 is set to a low-salt mode, the food and beverage information presentation unit 16 proposes to the user 98, for example, a recipe for low-salt miso soup or a lunch box menu with low salt content for breakfast or lunch when the user is sensitive to saltiness. When the user data 27 is set to a low-sugar mode, the food and beverage information presentation unit 16 proposes to the user 98, for example, bitter chocolate with low sugar content, when the taste state of the user 98 is estimated to be a state in which sweetness is strongly felt. This allows the food and beverage information presentation unit 16 to propose to the user 98 information on food and beverage that is suitable for the current taste state of the user 98 and is also satisfactory from the viewpoint of nutritional intake. This allows the device 100 to naturally guide the user 98 to, for example, low-salt menus or low-sugar menus, and to propose a menu of food and beverages that the user 98, for example, who has a decreased appetite, can feel is delicious.

[0034] Furthermore, the food and beverage information presentation unit 16 can present information about food and beverages that corresponds to the taste state of the user 98 based on information fed back from those who used the presented information about the food and beverages (including the user 98 and other users), which information is feedback regarding the taste evaluation or satisfaction level for the presented food and beverages, and the estimated taste state data 25.

[0035] The feedback information acquisition unit 17 acquires information fed back to the device 100 from a person (including the user 98 and other users) who has used the information on food and drink according to the taste state. The information fed back to the device 100 is, for example, information from a person who has used the information on food and drink presented by the food and drink information presentation unit 16, and includes, for example, information on the evaluation of taste and satisfaction with the presented recommended menu and the recipe of the menu. These pieces of feedback information are input to the device 100, for example, via the input unit 31 or the communication I / F unit 33. In this embodiment, the feedback information acquisition unit 17 updates the food and drink database 26 using these pieces of feedback information on food and drink presented by the food and drink information presentation unit 16. The acquired feedback information can be used by the food and drink information presentation unit 16. This allows the food and drink information presentation unit 16 to present information on food and drink according to the preferences and taste variation range of many users to the user 98. This optimizes the information on food and drink presented to the user 98 by the food and drink information presentation unit 16.

[0036] The auxiliary storage device 20 is a non-volatile storage device that stores an operating system (OS), various control programs, data generated by the programs, etc., and is configured, for example, by a flash memory, an eMMC (embedded multi media card), an SSD (solid state drive), etc. In this embodiment, the auxiliary storage device 20 stores health evaluation value data 21, time information data 22, sensory evaluation value data 23, an estimation model 24, taste state data 25, a food and drink database 26, user data 27, and a taste state estimation program 29.

[0037] The health evaluation value data 21 and the time information data 22 are real-time information when estimating the taste state of the user 98 (taste state data 25), and the food and drink database 26 and the user data 27 are information accumulated in the device 100. In this embodiment, the food and drink database 26 and the user data 27 are stored in the auxiliary storage device 20 in advance before estimating the taste state of the user 98. The sensory evaluation value data 23 is information acquired from a plurality of evaluators 198 when conducting a taste test in a human population to create an estimation model 24.

[0038] In the present embodiment, the estimation model 24 includes five associations. The first association represents an association between the insomnia score and a sensory evaluation value related to (the transition of) the aftertaste of taste. Preferably, the target taste in the first association includes at least one of sweetness, sourness, and umami. The second association represents an association between the insomnia score and a sensory evaluation value related to taste preference. Preferably, the target taste in the second association includes sweetness. The third association represents an association between the insomnia score and a sensory evaluation value related to the taste evaluation of the taste. Preferably, the target taste in the third association includes at least one of saltiness and bitterness. The fourth association represents an association between the circadian rhythm of taste and a sensory evaluation value related to the intensity of taste. Preferably, the target taste in the fourth association includes at least one of sweetness and bitterness. The fifth association represents an association between the circadian rhythm of taste and a sensory evaluation value related to the recognition ability (cognitive threshold) of taste. Preferably, the taste targeted in the fifth correlation includes at least one of bitterness and umami. The five correlations included in the estimation model 24 correspond to the following examples. The first correlation is based on Fig. 11(A) to Fig. 11(C). The second correlation is based on Fig. 12. The third correlation is based on Fig. 13(A) and Fig. 13(B). The fourth correlation is based on Fig. 9(A) and Fig. 9(B). The fifth correlation is based on Fig. 10(A) and Fig. 10(B). The estimation model 24 can be realized, for example, as a computer program. For example, when the estimation model 24 is realized as a computer program, the computer program is programmed to show the trends shown in each of the above-mentioned five correlations.

[0039] The food and drink database 26 is a database relating to various foods and drinks, and is input to the device 100 via, for example, the input unit 31 or the communication I / F unit 33, and is stored in advance in the auxiliary storage device 20. In this embodiment, the food and drink database 26 includes, as database items, information regarding the name, image, price, nutritional components, and recipe information of each food and drink. The information regarding nutritional components may include information regarding dietary reference intakes. The recipe information may include information regarding the name of the dish, ingredients, cooking steps, and a URL (Uniform Resource Locator) of a website relating to the food and drink. The website may include video information regarding the food and drink.

[0040] The food and drink database 26 can further include information on taste evaluation and satisfaction with respect to the food and drink as database items. The information on taste evaluation and satisfaction is feedback information acquired from the feedback information acquisition unit 17, and is updated using information fed back to the device 100 from a person (including the user 98 and other users) who has used the information on the food and drink according to the taste state presented by the food and drink information presentation unit 16.

[0041] When the food or beverage is an agricultural product, the food or beverage database 26 functions as the agricultural product database 26. Like the food or beverage database 26, the agricultural product database 26 includes the name, image, price, nutritional content, and recipe information of the agricultural product as database items. The agricultural product database 26 may further include information on the origin and variety of the agricultural product. The agricultural product database 26 may further include information on the taste evaluation and satisfaction level of the agricultural product.

[0042] The user data 27 is data related to the user 98, and is input to the device 100 via, for example, the input unit 31 or the communication I / F unit 33, and is stored in advance in the auxiliary storage device 20. In this embodiment, the user data 27 includes information related to the age, sex, number of working days, lifestyle, and food preference of the user 98. The information related to lifestyle is, for example, information related to whether or not the user works in shift work and daily wake-up time, specifically, "I have night shifts" or "I wake up around 6:00 in the morning". The information related to food preference is, for example, a low-salt mode related to saltiness, a low-sugar mode related to sweetness, a strong mode or a light mode related to seasoning, etc.

[0043] The taste state estimation program 29 is a computer program for implementing each of the units 11 to 17 in the data processing unit 10, which is a software functional block. The program 29 can be installed in the device 100 via a network 39, such as the Internet, connected by the communication I / F unit 33. Alternatively, the program 29 can be installed in the device 100 by having the device 100 read a computer-readable, non-transitory, tangible recording medium, such as a memory card, on which the program 29 is recorded.

[0044] The input unit 31 can be configured with, for example, a mouse and a keyboard, and the display unit 32 can be configured with, for example, a liquid crystal display and an organic EL display. The communication I / F unit 33 transmits and receives data to and from an external device via a wired or wireless network. The communication I / F unit 33 can be configured with various wired or wireless connections such as Ethernet (registered trademark), Wi-Fi (registered trademark), and Bluetooth (registered trademark). The input unit 31 and the display unit 32 may be integrated to be realized as a touch panel type display device.

[0045] [Processing Procedure] FIG. 4 is a flowchart showing a taste state estimating method according to one embodiment of the present invention.

[0046] The processes of steps S1 to S4 shown in FIG. 4 are respectively executed by the functional blocks of the data processing unit 10 (that is, by the taste state estimating device 100).

[0047] In this embodiment, basic data on the user 98 is acquired in advance prior to the processing of steps S1 to S4. In this embodiment, the basic data on the user 98 is the user data 27. When the user 98 uses the service of estimating a taste state provided by the device 100, the user 98 performs user registration via the device 100. For example, during user registration, the user 98 answers questions on basic data items (e.g., age, sex, number of working days, lifestyle, food preferences, etc.) according to the user registration guidance displayed on the display unit 32. The answers are input to the device 100 via the input unit 31 and recorded as the user data 27. Such input of the user data 27 may be performed at the time of user registration as exemplified, or may be performed each time the processing of steps S1 to S4 is started. The user 98 can input or update some or all of the data items of the user data 27.

[0048] In step S1, health evaluation value data 21 is obtained regarding the health condition of the user 98. In step S2, time information data 22 at which the user 98 responded to the health evaluation is obtained.

[0049] In step S3, the taste state of the user 98 is estimated based on the estimation model 24, and the health evaluation value data 21 and time information data 22 of the user 98. In step S4, information on food and drink according to the taste state of the user 98 is presented based on the estimated taste state data 25.

[0050] As described above, according to one embodiment of the present invention, an improved method, device, and program for estimating a human gustatory state taking into account fluctuations in the human sense of taste and smell can be provided. A person's taste sensitivity and desire (preference) for each taste are affected by the person's physical condition and time of day. In one embodiment of the present invention, the gustatory state of a user 98 is estimated from the health condition of the user 98 based on an estimation model including the correlation between a health evaluation value in a human population and a sensory evaluation value related to taste. This makes it possible to estimate the gustatory state of the user 98 taking into account fluctuations in the user's sense of taste and smell.

[0051] Furthermore, in one embodiment of the present invention, information on food and drink that corresponds to the taste state of the user 98 is presented based on the estimated taste state. This makes it possible to provide the user 98 with information on delicious food and drink that will provide a high level of satisfaction in a meal, taking into account the fluctuations in the user's 98 sense of taste and smell.

[0052] [Other formats] Although the present invention has been described above with reference to specific embodiments, the present invention is not limited to the above-described embodiments.

[0053] Fig. 5 and Fig. 6 are schematic diagrams for explaining the flow of data processing in a gustatory state estimating device according to one embodiment of the present invention. Fig. 5 is a diagram in the case where the gustatory state estimating device handles information on food and drink. Fig. 6 is a diagram in the case where the gustatory state estimating device handles information on agricultural products as information on food and drink. Fig. 7 is an example of data display or data input in the gustatory state estimating device shown in Fig. 5.

[0054] In the above embodiment, the gustatory state estimation device 100 estimates the gustatory state of the user 98 and presents information about food and drink corresponding to the gustatory state of the user 98 based on the estimated gustatory state, but the types of food and drink presented by the device 100 are not limited. As illustrated in Fig. 5, the device 100 can present information about various types of food and drink corresponding to the gustatory state of the user 98. In another embodiment, as illustrated in Fig. 6, the device 100 can present information about various types of agricultural produce corresponding to the gustatory state of the user 98.

[0055] As shown in FIG. 6, the aspect of presenting information on agricultural products can be combined with a known online ordering and sales system for agricultural products. This allows the device 100 to not only present information on agricultural products according to the taste state of the user 98, but also to accept an order for the presented agricultural products and deliver the agricultural products for which the order has been accepted to the user 98. The agricultural products delivered to the user 98 are agricultural products according to the taste state of the user 98, and it is possible to deliver agricultural products as ingredients custom-made for the user 98 to the user 98. Such a known online ordering and sales system is not limited to the aspect of presenting information on agricultural products shown in FIG. 6, but can also be combined with the aspect of presenting information on food and beverages shown in FIG. 5. That is, the device 100 not only presents information on food and beverages according to the taste state of the user 98, but also accepts an order for the presented food and beverages (for example, an order for a lunch box with low salt content) and delivers the accepted order (the lunch box in this example) to the user 98.

[0056] In the above embodiment, the device 100 uses the time information when the user 98 answers the health evaluation to estimate the taste state, but such time information by the user 98 is not essential information but is optional information for the device 100 to estimate the taste state. The device 100 can estimate the taste state without using the time information when the user 98 answers the health evaluation.

[0057] In the above embodiment, when estimating the taste state, the user 98 inputs a health evaluation value related to his / her own health condition to the device 100 by inputting an answer to a question related to health evaluation to the device 100 via the input unit 31, but the manner in which the health evaluation value is input to the device is not limited to this. The answer to the question related to health evaluation may be, for example, data previously answered by the user 98, which may be acquired from the external server 97 via the network 39. Instead of the answer to the question related to health evaluation, the biometric data of the user 98 (e.g., biorhythm, fatigue level, working hours, sleeping hours, number of steps, heart rate, blood pressure, etc.) may be automatically measured via a wearable smart device (e.g., a smart watch) worn by the user 98, and a part or all of the automatically measured biometric data may be input to the device 100. In this case, the device 100 may appropriately reinterpret or convert the acquired biometric data of the user 98 and use it as the health evaluation value of the user 98. Such modified forms of inputting health evaluation values ​​into the device are not limited to the case of estimating a taste state as described above, but also apply to the case where multiple evaluators 198 input their own health evaluation values ​​into the device 100 in a taste test for creating an estimation model 24.

[0058] In the above embodiment, the tastes to be subjected to the sensory evaluation are five tastes, namely sweetness, saltiness, sourness, bitterness, and umami (five tastes), but the tastes to be subjected to the sensory evaluation are not limited to these five tastes. The tastes to be subjected to the sensory evaluation do not need to include all five tastes, and may be, for example, four tastes, namely, sweetness, saltiness, sourness, and bitterness, or may include at least one of these five tastes. In addition to these exemplified tastes, the taste to be subjected to the sensory evaluation may further include flavor, deliciousness, and aroma. The meaning of taste in this specification includes the usual meaning of taste, as well as the aroma and flavor (smell), appearance (sight), texture (touch), and chewing sound (hearing) that are recognized in conjunction with taste, and should also be understood as a composite sensation (e.g., deliciousness) in which these elements are combined. In the example shown in the examples described later, for example, in the case of bitter chocolate, the aroma is, for example, a sweet aroma or a cacao aroma, and the flavor is, for example, an oily and fat feeling. In the case of dry sausage, for example, the aroma is, for example, a smoked aroma, and the flavor is, for example, a spicy feeling, a meaty flavor, or a greasy feeling.

[0059] In the above embodiment, the questions regarding health evaluation are questionnaires regarding fatigue, but the questions regarding health evaluation are not limited to this. In other embodiments, the questions regarding health evaluation can be three types, for example, the Chalder Fatigue Scale, the Athens Sleep Scale, and the General Health Questionnaire, and in still other embodiments, the questions regarding health evaluation are not limited to these three types. The questions regarding health evaluation may be any content that can determine the health evaluation value regarding the health state of the user 98 and the evaluator 198. For example, questions regarding fatigue can be questions other than the exemplified Chalder Fatigue Scale. Similarly, questions regarding insomnia can be questions other than the exemplified Athens Sleep Scale, and questions regarding physical and mental health states can be questions other than the exemplified General Health Questionnaire.

[0060] In the above embodiment, the gustatory state estimation device 100 is realized as an integrated device, but the gustatory state estimation device 100 does not have to be an integrated device, and the processor, memory, auxiliary storage device 20, etc. may be located in different places and connected to each other via a network. The input unit 31 and the display unit 32 also do not necessarily have to be located in one place, and may be located in different places and connected to each other so as to be able to communicate with each other via a network.

[0061] In the above embodiment, the functional blocks 11-17 constituting the data processing unit 10 are realized by software, but these functional blocks 11-17 may be realized in part or in whole as hardware. The processing of the functional blocks 11-17 constituting the data processing unit 10 does not need to be processed by a single processor, and may be distributed and processed by multiple processors. The functions of the data processing unit 10 and the data items in the auxiliary storage device 20 may be cloud-based in part or in whole in an external server device 37 connected via the communication I / F unit 33.

[0062] The following examples of the present invention will make the features of the present invention clearer. EXAMPLES

[0063] In Example 1, a taste test was conducted in a human population, and the relationship between the sensory evaluation of taste in the human population, the health evaluation value, and the circadian rhythm of taste was considered. The taste test was conducted by multiple evaluators for multiple types of food and drink.

[0064] <Method> The taste test was conducted three times, in the morning (8:00 AM), afternoon (12:00 PM), and evening (7:00 PM), on 19 research participants (ages 20-50). The amount of saliva produced by the research participants was measured before the taste test. The research participants refrained from eating, drinking coffee, or other leisure items for two hours before the start of the test. Five aqueous solutions with five different concentrations, as shown in Figure 8, were used in the test. Five aqueous solutions with five different concentrations were prepared and used for each of the five tastes (sweet, salty, sour, bitter, and umami).

[0065] Taste Intensity, Discrimination Ability, and Preference Tests The research collaborators put the solutions in their mouths in order of decreasing concentration and rated the intensity of the taste they detected from 0 to 5 (0: no taste, 1: very weak taste, 2: weak taste, 3: moderate taste, 4: strong taste, 5: very strong taste). The taste intensity test was rated on a 6-point scale from 0 to 5. If the participants rated the strength as 1 or higher, they answered which of the five taste categories (sweet, salty, sour, bitter, and umami) the solution tasted. Based on the answers, the concentration of the solution with the lowest concentration that allowed them to correctly answer the taste was recorded. The taste discrimination test was rated on a 5-point scale from 1 to 5. Furthermore, the research collaborators selected one solution with the most preferred (or in another embodiment, not unpleasant and acceptable) concentration from the five solutions with five different concentrations. The taste preference test was rated on a 5-point scale from 1 to 5.

[0066] Aftertaste test The research participant placed about 15 ml of the most highly concentrated aqueous solution in Figure 8 into their mouth and tasted it thoroughly with their entire mouth. After about 10 seconds, they spat out the solution, and evaluated the aftertaste every 10 seconds for 120 seconds. The evaluation was done using a 12 cm line scale. The aftertaste test was a stepless evaluation between 0 and 12. The aftertaste test was done for each of the five tastes.

[0067] Physical condition evaluation After the evening taste test, the participants answered three questionnaires about fatigue, insomnia, and mental and physical health over the past week. Fatigue was asked using the Chalder Fatigue Scale (evaluated on a scale of 0 to 33, with a score of 16 or more indicating possible chronic fatigue). Insomnia was asked using the Athens Sleep Scale (evaluated on a scale of 0 to 24, with a score of 6 or more indicating possible insomnia). Mental and physical health was asked using the General Health Questionnaire GHQ-28 (evaluated on a scale of 0 to 28, with a score of 6 or more indicating possible poor mental health). Mental and physical health includes the mental state, which is the state of the mind, and the physical health, and the GHQ-28 can capture four symptoms: physical symptoms, anxiety / insomnia, impaired social activities, and depression.

[0068] Taste evaluation The research participants tasted both the bitter chocolate and the dry sausage, and evaluated the aroma, taste, flavor, and deliciousness of each. The taste evaluation was done on a continuous scale ranging from 0 to 12. A 12 cm (120 mm) line scale was also used for the taste evaluation. The position on the line scale where the research participant made a mark was measured in millimeters (mm) and used as an evaluation score. For example, if the research participant could not smell anything at all, the score would be 0, and if the research participant smelled a very strong aroma, the score would be 120.

[0069] <Result> -Regarding the circadian rhythm of taste In the taste intensity test, a circadian rhythm was observed for sweetness and saltiness. The taste intensity rating for a low-concentration sweet solution (concentration 1: 0.125%) was significantly lower at night than during the day (P<0.05, Figure 9(A)). For bitterness, the intensity ratings for all concentrations were lower at night than during the day (P<0.05, Figure 9(B)).

[0070] Furthermore, when we looked at the concentration at which the type of taste could be accurately recognized (cognitive threshold), for bitterness, a lower concentration was recognized as a bitter aqueous solution in the daytime compared to the morning and evening (P<0.05, Figure 10(A) left). This result showed that bitterness sensitivity increased in the daytime, and as a result, the acceptable concentration of bitterness was lower in the daytime compared to the evening (P<0.05, Figure 10(A) right). On the other hand, for umami, taste sensitivity decreased in the daytime (P<0.05, Figure 10(B) left), and it became clear that a higher concentration umami aqueous solution was preferred (P<0.05, Figure 10(B) right).

[0071] Regarding taste and physical discomfort Regarding insomnia, 18 subjects were analyzed, excluding 1 subject with incomplete data, and 8 out of 18 subjects were found to have a tendency toward insomnia. When the results of the aftertaste test (daytime data) were compared between the healthy group (10 subjects) and the insomnia group (8 subjects), it was found that the aftertaste of sweetness and umami in the insomnia group tended to disappear faster than in the healthy group (P<0.10, Figure 11(A) and Figure 11(B)). For sourness, the strength of the aftertaste after 40 to 80 seconds was significantly lower in the insomnia group (P<0.05, Figure 11(C)). This result suggests that insomnia may have accelerated the disappearance of tastes in the oral cavity. In addition, the insomnia group preferred a lower concentration sweet solution than the healthy group (P<0.05, Figure 11), indicating a decreased preference for sweetness.

[0072] In a taste evaluation of bitter chocolate (approximately 32% fat, approximately 72% cacao) conducted at lunchtime, the insomnia group tended to have lower ratings for saltiness and melting in the mouth (P<0.10, Figure 13(A)). In a taste evaluation of dry sausage, the insomnia group also tended to have lower ratings for saltiness (P<0.10, Figure 13(B)), and lower ratings for bitterness and spiciness (P<0.05, Figure 13(B)).

[0073] <Example of a model showing the effect of evaluator state and evaluation time on taste and taste preference> 14 to 16 are examples of models showing the influence of the evaluator's condition (physical condition) on taste and taste preference. These illustrated models were created by analyzing the results of the taste test in this Example 1. Stepwise multiple regression analysis was used to analyze the relationships between the factors. Factors with a large influence between factors are shown in FIG. 14, those with a medium influence are shown in FIG. 15, and those with a small influence are shown in FIG. 16. In the following description, the ability to detect taste means the ability to detect the presence of a certain taste, and the ability to recognize taste means the ability to accurately recognize which taste the detected taste is, for example, of the five tastes.

[0074] Referring to Figure 14, we consider the model with the greatest influence. When the evaluator is sleepless, the aftertaste disappears more quickly. When the evaluator is mentally fatigued, the ability to detect weak flavors decreases, and the evaluation value of the intensity of strong flavors (subjective taste intensity across the five tastes) also decreases, resulting in a lower taste evaluation value. Note that the path values ​​shown in the model are standard partial regression coefficients, ** :p<0.01.

[0075] Referring to Figure 15, a model with a medium degree of influence will be considered. When the evaluator feels physically tired, their ability to detect flavors increases and the aftertaste tends to linger, leading to a higher taste evaluation value. When the evaluator feels physically tired or feels that their daily activities (work, etc.) are stalled, their preference for saltiness increases. On the other hand, when the evaluator's physical health is declining (headache, fatigue, etc.), their preference for saltiness, sourness, and umami decreases. When their mental health is declining (anxiety, insomnia), their preference for sweetness decreases. Note that the path values ​​shown in the model are standard partial regression coefficients, ** :p<0.01.

[0076] Referring to Figure 16, we consider a model with a small effect. If the evaluator produces a lot of saliva, the aftertaste disappears more quickly. If the evaluator's body temperature is high, their ability to detect flavors increases, so they can detect even weak flavors (low concentrations). On the other hand, if the evaluator's body temperature is high, their preference for sweetness decreases. If the evaluator is feeling insomnia, their preference for umami increases. Note that the path values ​​shown in the model are standard partial regression coefficients, * :p<0.05.

[0077] <Example of a model showing the relationship between evaluator's condition (physical condition) and sensory evaluation> Fig. 17 is an example of a sensory evaluation model showing the influence of environmental factors such as evaluation time and room temperature, and poor physical condition such as insomnia on the taste. The illustrated model was created by analyzing the results of the taste test in this Example 1, in which dry sausage was used as the sample. Stepwise multiple regression analysis was used to analyze the relationships between each factor.

[0078] Consider the sensory evaluation model shown in Figure 17. The factor that had a major impact on the taste of dry sausage was "how easily the aftertaste lingers." Aftertaste was significantly reduced by insomnia, and it was shown to contribute not only to lowering the strength of the food's saltiness and sourness, but also to the strength of the meat's flavor and oiliness. Furthermore, sourness and meat flavor, which are influenced by the aftertaste, also influenced the overall evaluation score of the food's "deliciousness." On the other hand, it was suggested that a decline in mental health, as indicated by anxiety and insomnia, may reduce preference for sweetness, indirectly lowering the evaluation score of deliciousness. Note that the path values ​​shown in the model are standard partial regression coefficients. * :p<0.05, ** :p<0.01. [Explanation of symbols]

[0079] 10 Data Processing Section 11 Health evaluation value acquisition section 12 Time information acquisition section 13 Sensory evaluation value acquisition unit 14 Estimation Model Creation Department 15 Taste state estimation unit 16 Food and Beverage Information Presentation Department 17 Feedback information acquisition section 20 Auxiliary storage 21 Health evaluation data 22 Time information data 23 Sensory evaluation data 24 Estimation model 25 Taste state data 26 Food and Beverage Database (Agricultural Products Database) 27 User Data 29 Taste state estimation program 31 Input section 32 Display section 33 Communication interface section (communication I / F section) 37 Server equipment 39 Network 71-75 Input dialog box for taste testing 81 Input Dialog Box 82,83 Output dialog box 97 Server equipment (cloud server) 98 User 100 Taste state estimation device 198 Taste Test Evaluators 199 Food and drink for taste testing

Claims

1. A taste state estimation method executed by an apparatus having a processor, comprising: acquiring a health evaluation value relating to a health condition of a user; estimating a taste state of the user based on an estimation model including a correlation between a health evaluation value and a sensory evaluation value related to taste in a human population and the health evaluation value; A taste state estimation method comprising:

2. 2. The method of claim 1, wherein the taste state includes information regarding at least one selected from the group consisting of taste intensity, taste preference, taste aftertaste, taste detection ability, taste recognition ability, and taste evaluation.

3. The method of claim 1 , wherein the health condition comprises at least one selected from the group consisting of fatigue, insomnia, and physical and mental health conditions.

4. The estimation model is A first correlation representing a correlation between an insomnia score and a sensory evaluation value related to a taste aftertaste; A second correlation representing a correlation between the insomnia score and the sensory evaluation value regarding taste preference; and A third correlation representing a correlation between the insomnia score and a sensory evaluation value related to taste evaluation; The method of claim 1 , comprising at least one of:

5. The method further includes the step of obtaining information regarding a time period of use; The estimation model further includes a correlation between the circadian rhythm of taste in a human population and a sensory evaluation value related to taste, The method according to claim 1 , wherein the step of estimating the taste state estimates the taste state of the user further based on information about the time period of use.

6. The estimation model is A fourth correlation expressing a correlation between the circadian rhythm of taste and a sensory evaluation value regarding taste intensity; A fifth correlation represents a correlation between the circadian rhythm of taste and a sensory evaluation value related to taste recognition ability; The method of claim 5 , comprising at least one of:

7. The method of claim 1 , wherein the estimation model includes an association between a circadian rhythm of taste, a health evaluation value, and a sensory evaluation value related to taste in a human population.

8. A food and beverage suggestion method executed by an apparatus having a processor, comprising: Each step of a taste state estimating method according to claim 1 for estimating a taste state of a user; presenting information about food and drink according to the user's taste state based on the estimated taste state; The food and beverage suggestion method includes:

9. The method according to claim 8 , wherein the information about the food or drink includes at least one selected from the group consisting of the name, image, price, place of origin, variety, nutritional components, and recipe information of the food or drink.

10. The method according to claim 8, wherein the step of presenting information about food and beverages comprises comparing the estimated taste state with a food and beverage database storing information about food and beverages, thereby presenting information about food and beverages that corresponds to the user's taste state.

11. The method according to claim 8, wherein the step of presenting information regarding the food and beverages is based on information fed back from a person who has used the presented information regarding the food and beverages, and information regarding the food and beverages corresponding to the user's taste state is presented based on the information fed back regarding the taste evaluation or satisfaction level for the food and beverages and the estimated taste state.

12. The method of claim 8, wherein the food or beverage is an agricultural product.

13. a health evaluation value acquiring means for acquiring a health evaluation value related to a health state of a user; a taste state estimation means for estimating a taste state of the user based on an estimation model including a correlation between a health evaluation value and a sensory evaluation value related to taste in a human group and the health evaluation value; A taste state estimation device comprising:

14. Each unit of the taste state estimating device according to claim 13 for estimating a taste state of a user; a means for presenting information about food and drink according to the user's gustatory state based on the estimated gustatory state; A food and beverage recommendation device comprising:

15. A program for causing a computer to execute each step of the method according to any one of claims 1 to 12.

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