A method for obtaining food evaluations, a system for obtaining food evaluations, a device for obtaining food evaluations, a program for obtaining food evaluations, and a recording medium on which the same is recorded.

Abstract

This invention provides a method for obtaining food evaluations that can appropriately acquire the evaluations of consumers of food products. [Solution] In the food evaluation acquisition method, the processing unit 4 acquires brainwaves before and during consumption when the eater consumes the food while being able to move their upper body freely and consume the food at their preferred timing. Brainwave index values ​​are obtained as deviations from these values, and evaluation data is acquired using the brainwave index values ​​and a learning model (STEP 1-4).

Description

[Technical Field]

[0001] The present invention relates to a food evaluation acquisition method, a food evaluation acquisition system, a food evaluation acquisition device, a food evaluation acquisition program, and a recording medium having the program recorded thereon. [Background Art]

[0002] Conventionally, as a method for acquiring evaluation of food, the one described in Patent Document 1 is known. In this evaluation acquisition method, the breathing time of an eater during eating and drinking and the breathing time immediately after swallowing are acquired as respiratory parameters, and based on a graph or the like showing the correlation between the respiratory parameters and sensory evaluation data, the eater's sensory evaluation of the food is acquired. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent No. 7195388 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] According to the above-mentioned conventional food evaluation acquisition method, it is necessary to attach a temperature sensor to the nose of the eater in order to measure the breathing time of the eater, and it is necessary to attach a surface electrometer to the surface of the throat of the eater in order to acquire the opening timing and swallowing timing of the eater. As a result, the eater feels discomfort and inconvenience due to the attachment of these devices and the restriction of their behavior, which may cause the correlation between the respiratory parameters and the sensory evaluation data to deviate from the actual relationship. As a result, there is a possibility that the eater's sensory evaluation of food cannot be appropriately acquired.

[0005] The present invention has been made to solve the above problems and aims to provide a method for obtaining food evaluations, a food evaluation system, a food evaluation device, a food evaluation program, and a recording medium on which the same can be recorded, which can appropriately obtain the evaluations of consumers of food. [Means for solving the problem]

[0006] To achieve the above objective, the method for obtaining an evaluation of food according to claim 1 is characterized in that a processing unit performs the following steps: a first bioparameter acquisition step of acquiring a first bioparameter, which is a bioparameter indicating the state of the eater's bodily reaction before eating when the eater eats food in a predetermined state without restrictions on predetermined actions and conditions; a second bioparameter acquisition step of acquiring a second bioparameter, which is a bioparameter during eating when the eater eats food in a predetermined state; an index value acquisition step of acquiring an index value representing the magnitude relationship between the first bioparameter and the second bioparameter; a model representing the correlation between the index value and evaluation data including sensory evaluation when the eater eats food in a predetermined state; and an evaluation data acquisition step of acquiring evaluation data using the index value.

[0007] According to this method for evaluating food, a first bioparameter and a second bioparameter are obtained, index values ​​are obtained based on the first and second bioparameters, and evaluation data is obtained using the model and index values. In this case, the first and second bioparameters are parameters that indicate the state of the eater's bodily reactions before and during consumption when the eater consumes food under predetermined conditions without restrictions on predetermined actions and conditions. Therefore, these first and second bioparameters are obtained in a manner that avoids causing the eater discomfort or inconvenience, and thus appropriately represent the state of the eater's bodily reactions when actually consuming food.

[0008] In addition, experiments conducted by the applicant have confirmed that an index value representing the relative magnitudes of the first and second biological parameters has a high correlation with evaluation data, including sensory evaluations, when consumers consume food under predetermined conditions. Therefore, by using a model that represents the correlation between the index value and evaluation data, including sensory evaluations, when consumers consume food under predetermined conditions, it is possible to obtain consumers' evaluation data of food appropriately and accurately.

[0009] In the present invention, the biological parameters are preferably the electroencephalogram (EEG) or pupil diameter of the person who has consumed food or drink.

[0010] Experiments conducted by the applicant have confirmed that when the electroencephalogram (EEG) or pupil diameter of the person consuming the food is used as a biological parameter, an index value representing the relationship between the magnitude of a first biological parameter before consuming the food and a second biological parameter during consuming the food shows a high correlation with evaluation data, including sensory evaluation, when the person consuming the food under predetermined conditions without restrictions on predetermined actions or conditions. Therefore, this method for obtaining food evaluations allows for the accurate and appropriate acquisition of evaluation data from people consuming food.

[0011] In the present invention, it is preferable that the brainwaves of the person eating and drinking are measured by a wearable measuring device that can be attached to the person's head, and the pupil diameter is measured by a wearable measuring device that can be attached to the person's face.

[0012] According to this food evaluation method, the brainwaves of the person consuming the food are measured by a wearable measuring device that can be attached to the person's head, and the pupil diameter is measured by a wearable measuring device that can be attached to the person's face. Therefore, the person consuming the food can do so without any restrictions on movement of their entire body, including their head, and biological parameters can be obtained while avoiding any discomfort or inconvenience for the person consuming the food.

[0013] In the present invention, the biological parameter is the brainwave of the person eating, the food is food that requires chewing, and it is preferable that the brainwave during the consumption of the food is acquired after filtering out noise caused by the person's chewing.

[0014] This method for evaluating food allows for the acquisition of brainwave data during food consumption while avoiding the influence of noise generated when consumers chew food. As a result, accurate and appropriate evaluation data of consumers regarding food can be obtained.

[0015] In the present invention, the predetermined state is preferably one in which the eater can move their upper body without restriction and the timing of the eater's consumption of food is not restricted.

[0016] This method for evaluating food allows consumers to consume food at their own pace and with the freedom to move their upper bodies as they wish. This enables the acquisition of biological parameters without causing discomfort or restriction to the consumer, and allows for the accurate and appropriate acquisition of consumer evaluation data of the food.

[0017] In the present invention, it is preferable that in the first bioparameter acquisition step and the second bioparameter acquisition step, the eater's brainwaves or pupil diameter are acquired as the first bioparameter and second bioparameter while the eater is experiencing either a virtual space, a mixed reality space, or augmented reality through the experience device.

[0018] According to this method for obtaining evaluation data for food products, while the consumer is experiencing either a virtual space, a mixed reality space, or augmented reality through an experience device, the consumer's brainwaves or pupil diameter are acquired as the first and second bioparameters. This allows these biometric indicators to be acquired under stable environmental conditions, enabling accurate and appropriate acquisition of consumer evaluation data for food products.

[0019] To achieve the aforementioned objectives, the method for obtaining an evaluation of food according to claim 7 is characterized in that a arithmetic processing unit performs the following steps: a bioparameter acquisition step of acquiring bioparameters indicating the state of the eater's bodily reaction during consumption when the eater consumes food under predetermined conditions without restrictions on predetermined actions and conditions; a model representing the correlation between the bioparameters and evaluation data including sensory evaluation when the eater consumes food under predetermined conditions; and an evaluation data acquisition step of acquiring evaluation data using the bioparameters.

[0020] According to this method for evaluating food, bioparameters are obtained, and evaluation data is acquired using the model and bioparameters. In this case, since the bioparameters are parameters that indicate the state of the eater's bodily reactions during consumption when the eater consumes the food under predetermined conditions without restrictions on predetermined actions and conditions, these bioparameters are obtained in a manner that avoids causing the eater discomfort or inconvenience, and thus appropriately represent the state of the eater's bodily reactions when actually consuming the food.

[0021] In addition, experiments conducted by the applicant have confirmed that biological parameters have a high correlation with evaluation data, including sensory evaluations, when consumers consume food under predetermined conditions. Therefore, by using a model that represents the correlation between biological parameters and evaluation data, including sensory evaluations, when consumers consume food under predetermined conditions, it is possible to obtain consumers' evaluation data of food appropriately and accurately.

[0022] To achieve the aforementioned objectives, the food evaluation acquisition system of the present invention is characterized by being configured to perform any of the food evaluation acquisition methods described above.

[0023] To achieve the aforementioned objectives, the food evaluation device of the present invention is characterized by being configured to perform any of the above-described food evaluation methods.

[0024] To achieve the object described above, the food evaluation acquisition program of the present invention is characterized by causing a computer to execute any of the food evaluation acquisition methods described above.

[0025] To achieve the object described above, the recording medium of the present invention is characterized in that the food evaluation acquisition program described above is recorded thereon, and the food evaluation acquisition program is readable by a computer. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] [Figure 1] FIG. 1 is a block diagram showing the configuration of a food evaluation acquisition system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram showing a worn state of an electroencephalogram measurement device. [Figure 3] FIG. 3 is a diagram showing a worn state of a pupil diameter measurement device. [Figure 4] FIG. 4 is a diagram showing a food eating test state. [Figure 5] FIG. 5 is a diagram showing procedures, elapsed time and the like during a food eating test. [Figure 6] FIG. 6 is a flowchart showing acquisition processing of food evaluation data. [Figure 7] FIG. 7 is a diagram showing a worn state of a head mounted display and an electroencephalogram measurement device. DESCRIPTION OF THE EMBODIMENTS

[0027] Hereinafter, a food evaluation acquisition method and an evaluation acquisition system according to an embodiment of the present invention will be described with reference to the drawings. The evaluation acquisition system of the present embodiment acquires evaluation of food by the evaluation acquisition method described below, and as the evaluation of food, evaluation data including sensory evaluation when a consumer eats food (such as a delicious feeling described later) is used.

[0028] As shown in Figure 1, the evaluation acquisition system 1 of this embodiment includes an electroencephalogram (EEG) measuring device 2, a pupil diameter measuring device 3, and a calculation processing device 4. In this evaluation acquisition system 1, when a person consumes food, electroencephalograms or pupil diameter are used as biological parameters that indicate the state of the person's bodily response, and these electroencephalograms or pupil diameters are measured using the electroencephalogram measuring device 2 or the pupil diameter measuring device 3.

[0029] As shown in Figure 2, the electroencephalogram (EEG) measuring device 2 is a wearable type that can be attached to the head of the person eating M in the form of a headband, and is communicatively connected to the processing unit 4. In this embodiment, when the person eating M consumes food, the EEG measuring device 2 is attached to the head of the person eating M before the food is consumed, measures the brainwaves of the person eating M from before the start of consumption until during consumption, and transmits the measurement results to the processing unit 4.

[0030] In this case, since the electroencephalogram measuring device 2 is a wearable type that is attached to the head, the person eating / drinking (M) can eat food while being able to move their upper body freely without experiencing any restriction of movement or discomfort in the upper body, including the head.

[0031] Furthermore, as shown in Figure 3, the pupil diameter measuring device 3 is a wearable type that can be attached to the face of the person eating or drinking (M) and is connected to the processing unit 4 for communication. In this embodiment, when the person eating or drinking (M) consumes food, the pupil diameter measuring device 3 is attached to the face of the person eating or drinking (M) before the food is consumed, measures the pupil diameter of the person eating or drinking (M) from before the food is consumed until the food is consumed, and transmits the measurement results to the processing unit 4.

[0032] In this case, since the pupil diameter measuring device 3 is a wearable type that is attached to the face, the person eating or drinking M can eat food without experiencing any restriction of movement or discomfort in the upper body, including the head, and can move their upper body freely.

[0033] The arithmetic processing unit 4 is a server and includes a processor, storage, I / O interface, and communication circuitry (none of which are shown in the figure). The storage of the arithmetic processing unit 4 contains application software for performing various arithmetic operations, as well as the learning model, which will be described later.

[0034] As described later, the arithmetic processing unit 4 acquires evaluation data, including sensory evaluation of food by consumers, using the learning model and the electroencephalogram measurement results from the electroencephalogram measurement device 2, or the learning model and the pupil diameter measurement results from the pupil diameter measurement device 3. In this embodiment, the arithmetic processing unit 4 corresponds to the evaluation acquisition device, and the storage corresponds to the recording medium.

[0035] Furthermore, an external terminal 5 is connected to the arithmetic processing unit 4. This external terminal 5 is used by the user of the evaluation acquisition system 1 when acquiring evaluation data, as will be described later.

[0036] Next, the method for acquiring the learning model used to acquire evaluation data in this embodiment and its principle will be explained. In this embodiment, the following test method is used to acquire electroencephalogram (EEG) or pupil diameter data of the eater before and during the consumption of food, as well as subjective evaluation data of the eater. In this case, the subjective evaluation data of the eater is the presence or absence of "deliciousness," "comfort (a feeling of relief)," and "luxury / specialness" when consuming the food.

[0037] In this test method, the following six types of food are used as test foods: "somen noodles with two types of noodle soup," "two types of cooked beef steak," and "two types of mackerel simmered in miso." More specifically, the two types of noodle soup are from different manufacturers, the two types of cooked beef steak are domestic and imported, and the two types of mackerel simmered in miso are one with a strong flavor and the other with a strong broth flavor. Each of these foods is prepared in a roughly rectangular container with a lid.

[0038] Furthermore, dozens of women aged 20 to 50 were selected as subjects (consumers). In the first trial, these subjects consumed three of the six types of food mentioned above, and in the next trial, they consumed the remaining three types of food.

[0039] During this procedure, as shown in Figure 4, subject M1 sits in a chair while wearing the electroencephalogram (EEG) measuring device 2. After opening the lid of the container 6 on the table, he uses chopsticks 7 to eat the food 8 inside the container 6 at a time of his choosing. Subject M1 also eats the food in the same manner as in Figure 4 when wearing the pupil diameter measuring device 3.

[0040] In this study, the procedure and timeline for a subject to consume one type of food are as shown in Figure 5. Specifically, the period from time t0 to t1 is set as a resting period (e.g., several minutes) to ensure the subject is at rest while wearing the electroencephalogram (EEG) device 2 or pupillary diameter measuring device 3, and the period from time t1 to t2 is a recognition period (e.g., several seconds) for the subject to open the container lid and recognize the food.

[0041] Next, the period from time t2 to t3 is the preparation period during which the subject prepares to eat the food (e.g., a few seconds to tens of seconds), and the period from time t3 to t4 is the actual eating period during which the subject eats the food (e.g., a few minutes). Furthermore, the period from time t4 to t5 is the afterglow period during which the subject savors the post-meal taste (e.g., tens of seconds to a few minutes), and the period from time t5 to t6 is the evaluation period during which the subject makes a subjective evaluation of the food (e.g., a few seconds to tens of seconds). During this evaluation period, the subject evaluates the presence or absence of "deliciousness," "comfort (a feeling of relief)," and "luxury / specialness" as subjective evaluations, thereby obtaining these three types of evaluation data.

[0042] Furthermore, during the above tests, at times when the subject is in a resting state during the period t0-t1, or at times t2-t3 when the subject is preparing to eat the food, the electroencephalogram (EEG) or pupil diameter (Pupil diameter) is measured by the electroencephalogram (EEG) measuring device 2 or the pupil diameter measuring device 3. These EEG or pupil diameter measurements are obtained as the first biological parameters, which are biological parameters before food ingestion.

[0043] Furthermore, during the period from time t3 to t4, electroencephalogram (EEG) measurement device 2 or pupil diameter measurement device 3 measures either the electroencephalogram (EEG) or pupil diameter, and these EEG or pupil diameter measurement results are acquired as second biological parameters, which are biological parameters during food ingestion. In the case of EEG, the second biological parameters are acquired after filtering out noise during chewing through a predetermined filtering process.

[0044] Next, the difference between the first and second biological parameters is obtained as an index value. In the following explanation, the index value when the first and second biological parameters are electroencephalograms (EEGs) will be referred to as the "EEG index value," and the index value when the first and second biological parameters are pupil diameters will be referred to as the "pupil diameter index value."

[0045] Then, using the combination of the two types of index values ​​and three types of evaluation data obtained through the above tests as training data, the model parameters of a machine learning model (e.g., a neural network) are trained using a predetermined learning algorithm (e.g., gradient descent). As a result, the following six types of trained models are obtained as machine learning models whose model parameters have been trained (hereinafter referred to as "trained models").

[0046] In other words, when electroencephalogram (EEG) index values ​​are input, three types of learning models (hereinafter referred to as "EEG learning models") are acquired that output three types of evaluation data respectively. In addition, when pupil diameter index values ​​are input, three types of learning models (hereinafter referred to as "pupil diameter learning models") are acquired that output three types of evaluation data respectively.

[0047] Next, we will explain the process used in the processing unit 4 to acquire food evaluation data using the learned model acquired as described above. First, referring to Figure 6, we will explain using the case where electroencephalograms (EEGs) are used as the first and second biological parameters. In this case, the EEGs are acquired via the EEG measurement device 2 using the same method as in the test described above.

[0048] As shown in Figure 6, the process of acquiring the first biological parameter is performed first (Figure 6 / STEP1). In this process, the brainwaves of person M when their brainwaves are stable during the aforementioned rest period are acquired as the first biological parameter. Alternatively, the brainwaves of person M when their brainwaves are stable during periods unrelated to eating or drinking, other than the aforementioned rest period, may also be acquired as the first biological parameter.

[0049] Next, the process for acquiring the second biological parameter is executed (Figure 6 / STEP2). In this process, the electroencephalogram (EEG) during the actual eating period is acquired, and by applying a predetermined filtering process to this EEG, the EEG with chewing noise filtered out is acquired as the second biological parameter.

[0050] Next, the process of acquiring electroencephalogram (EEG) index values ​​is executed (Figure 6 / STEP3). In this process, EEG index values ​​are acquired as the difference between the first and second biological parameters.

[0051] Next, the evaluation data acquisition process is executed (Figure 6 / STEP4). In this process, three types of evaluation data are acquired using electroencephalogram (EEG) index values ​​and three types of EEG learning models. Specifically, evaluation data representing the presence or absence of "deliciousness," "comfort," and "luxury / specialness" is acquired.

[0052] When electroencephalography (EEG) is used as the first and second biological parameters, three types of evaluation data are obtained as described above.

[0053] On the other hand, when pupil diameter is used as the first and second biological parameters, the same processing as in STEP 1 to 4 in Figure 6 is performed to obtain evaluation data representing the presence or absence of "deliciousness," "comfort," and "luxury / specialness."

[0054] When pupil diameter is used as the first and second biological parameters, three types of evaluation data are obtained as described above.

[0055] Furthermore, when a user of the evaluation acquisition system 1 acquires evaluation data, the user operates the external terminal 5, which sends a signal requesting evaluation data to the processing unit 4. As a result, the aforementioned evaluation data is sent from the processing unit 4 to the external terminal 5, and the user can acquire the evaluation data. Consequently, the user can understand whether or not the diner M experienced a sense of "deliciousness," "comfort," and "luxury / specialness" when consuming the food.

[0056] As described above, according to the food evaluation acquisition method of this embodiment, first and second biological parameters are acquired when a diner M consumes food under predetermined conditions, an index value is acquired as the deviation of the first and second biological parameters, and evaluation data representing the presence or absence of "deliciousness," "comfort," and "luxury / specialness" is acquired using the learning model and the index value.

[0057] In this case, the predetermined state described above is a state in which the eater M can move their upper body freely and consume food at a time convenient for them, and the first and second bioparameters are the electroencephalogram or pupil diameter before and during consumption when the eater M consumes food in such a predetermined state. Therefore, these first and second bioparameters are acquired in a state that avoids causing the eater M discomfort and discomfort, and will appropriately represent the state of the body's reaction when the eater M actually consumes food.

[0058] In addition, experiments conducted by the applicant have confirmed that the index value, which is the difference between the first and second biological parameters, has a high correlation with the evaluation data when the eater M consumes food under the predetermined conditions. Therefore, by using a learning model that represents the correlation between the index value and the evaluation data when the eater M consumes food under the predetermined conditions, it is possible to obtain the eater M's evaluation data of food appropriately and accurately.

[0059] Furthermore, the brainwaves of person M are measured by a wearable measuring device that can be attached to person M's head, and pupillary movement is measured by a wearable measuring device that can be attached to person M's face. Therefore, person M can consume food without any restrictions on movement of the upper body, including the head, and the first and second biological parameters can be obtained while avoiding discomfort and limitations for person M.

[0060] Furthermore, if the biological parameter is electroencephalography (EEG), it is possible to acquire EEG data during food consumption while avoiding the influence of noise when the eater M chews the food, thereby enabling accurate and appropriate acquisition of the eater M's evaluation data of the food.

[0061] This embodiment uses three types of electroencephalogram (EEG) learning models that output three types of evaluation data when EEG index values ​​are input, and three types of pupil diameter learning models that output three types of evaluation data when pupil diameter index values ​​are input. However, instead, three types of learning models that output three types of evaluation data when EEG index values ​​and pupil diameter index values ​​are input may be used. In that case, the learning model can be obtained by using the combination of EEG index values, pupil diameter index values ​​and the three types of evaluation data as training data and learning the model parameters of the machine learning model.

[0062] Furthermore, as a learning model, a model may be used that represents the correlation between bioparameters indicating the state of the eater's physical response during eating when the eater consumes food under the aforementioned conditions, and evaluation data. In that case, as shown in Figure 6 above, steps 1 and 3 can be omitted, and in step 2, the eater's electroencephalogram (or pupil diameter) during eating can be acquired as a bioparameter, and in step 4, three types of evaluation data can be acquired using the bioparameter and the learning model.

[0063] In this case, experiments conducted by the applicant have confirmed that biological parameters have a high correlation with evaluation data, including sensory evaluations, when consumers consume food under predetermined conditions. Therefore, by using a model that represents the correlation between biological parameters and evaluation data, including sensory evaluations, when consumers consume food under predetermined conditions, it is possible to obtain consumers' evaluation data of food appropriately and accurately.

[0064] Furthermore, while the embodiment shows an example in which brain waves are acquired as a biological parameter while the person eating and drinking M is aware of the real space, as shown in Figure 7, a head-mounted display 10 (experience device) may be attached to the head of the person eating and drinking M in addition to the brain wave measurement device 2, and the brain waves or pupil diameter of the person eating and drinking M may be acquired while the person eating and drinking M is experiencing either a virtual space, a mixed reality space, or augmented reality via the experience device.

[0065] In this case, the environment of the consumer M's home is reproduced as one of the virtual space, mixed reality space, or augmented reality through the experience device. Furthermore, the learning model used is one whose model parameters have been trained using test data obtained while consumer M is experiencing one of the virtual space, mixed reality space, or augmented reality. With this configuration, consumer M can experience a relaxed feeling at home, allowing for the acquisition of consumer M's brainwaves or pupil diameter under stable environmental conditions. In addition, by keeping the surrounding environment constant, fluctuations in pupil diameter due to changes in the surrounding environment can be reduced, thereby enabling the accurate and appropriate acquisition of consumer M's evaluation data of the food.

[0066] Here, mixed reality represents an environment in which virtual objects are placed in real space in an interactive state, while augmented reality represents an environment in which virtual objects are placed in real space in an intangible state.

[0067] Furthermore, while the embodiment uses food that requires chewing when consumed, a beverage may be used instead as the food.

[0068] Furthermore, although the embodiment uses a server as the processing unit, instead, a combination of multiple servers or multiple personal computers may be used as the processing unit, or a combination of a server and a personal computer may be used, or a personal computer may be used alone.

[0069] On the other hand, while the embodiment uses the difference between the first biological parameter and the second biological parameter as the index value, the index value of the present invention is not limited to this, and can be any value that represents the magnitude relationship between the first biological parameter and the second biological parameter. For example, the index value may be the difference between the second biological parameter and the first biological parameter, the ratio between the first biological parameter and the second biological parameter, or the ratio between the second biological parameter and the first biological parameter.

[0070] Furthermore, while the embodiment uses a learning model as an example, the model of the present invention is not limited to this, and any model that represents the relationship between indicator values ​​and evaluation data is acceptable. For example, a database, map, or calculation formula that defines the relationship between indicator values ​​and evaluation data may be used as the model.

[0071] Although the illustrated embodiments have been described above, the present invention is not limited to these embodiments. For example, the above embodiments described a case in which the evaluation acquisition system 1 is a single computer system. However, the present invention also includes an evaluation acquisition program for causing any one or more computers to execute the aforementioned evaluation acquisition method, and a recording medium for recording the program and which allows the program to be read by a computer used by a user or the like. [Explanation of Symbols]

[0072] 1. Evaluation Acquisition System 2. Electroencephalogram (EEG) measuring device 3 Pupil diameter measuring device 4. Arithmetic Processing Unit 10. Head-mounted display (experiential device) M Eater

Claims

1. A first bioparameter acquisition step involves acquiring a first bioparameter, which is a bioparameter indicating the state of the eater's bodily reaction before eating food in a predetermined state without restrictions on predetermined actions and conditions. A second bioparameter acquisition step, which involves acquiring a second bioparameter, which is a bioparameter during consumption when the person consuming the food in the predetermined state, An index value acquisition step to obtain an index value representing the magnitude relationship between the first biological parameter and the second biological parameter, A model representing the correlation between the index value and evaluation data including sensory evaluation when the eater consumes the food under the predetermined conditions, and an evaluation data acquisition step of acquiring the evaluation data using the index value. A method for obtaining the evaluation of food products, characterized in that the evaluation is performed by a processing unit.

2. In the method for obtaining an evaluation of food according to claim 1, A method for evaluating food, characterized in that the aforementioned biological parameters are the electroencephalogram or pupil diameter of the person who consumed the food.

3. In the method for obtaining an evaluation of food according to claim 2, A method for evaluating food, characterized in that the brainwaves of the person consuming the food are measured by a wearable measuring device that can be attached to the head of the person consuming the food, and the pupil diameter is measured by a wearable measuring device that can be attached to the face of the person consuming the food.

4. In the method for obtaining an evaluation of food according to claim 1, The aforementioned biological parameters are the brainwaves of the person who consumed the food and drink. The aforementioned food is a food that requires chewing. A method for evaluating food, characterized in that the brainwaves during the consumption of the food are acquired after filtering out noise caused by the eater's chewing.

5. In the method for obtaining an evaluation of food according to claim 1, A method for obtaining an evaluation of food, characterized in that the predetermined state is a state in which the person eating or drinking can move their upper body without restriction and the timing of the person eating or drinking the food is not restricted.

6. In the method for obtaining an evaluation of food according to claim 1, A method for evaluating food, characterized in that, in the first bioparameter acquisition step and the second bioparameter acquisition step, the eater's brainwaves or pupil diameter are acquired as the first bioparameter and second bioparameter while the eater is experiencing either a virtual space, a mixed reality space, or augmented reality through an experience device.

7. A bioparameter acquisition step to acquire bioparameters indicating the state of the eater's bodily reactions during consumption when the eater consumes food under predetermined conditions without restrictions on predetermined actions and conditions, A model representing the correlation between the biological parameters and evaluation data including sensory evaluation when the eater consumes the food under the predetermined conditions, and an evaluation data acquisition step of acquiring the evaluation data using the biological parameters, A method for obtaining the evaluation of food products, characterized in that the evaluation is performed by a processing unit.

8. A food evaluation acquisition system characterized by being configured to perform the food evaluation acquisition method described in any one of claims 1 to 7.

9. A food evaluation device characterized by being configured to perform the food evaluation method described in any one of claims 1 to 7.

10. A food evaluation acquisition program characterized by causing a computer to execute the food evaluation acquisition method described in any one of claims 1 to 7.

11. A recording medium that records a food evaluation acquisition program described in claim 10, and is characterized in that the food evaluation acquisition program is readable by the computer.

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