Sensory characteristic information generation system, sensory characteristic information generation method, sensory characteristic information generation program

Abstract

This provides a novel technology for generating sensory characteristic information. [Solution] A sensory characteristics information generation system for an object, comprising: a cerebral blood flow information acquisition unit 50 that acquires information on cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex when a subject obtains sensations about an object; and a sensory characteristics information generation unit 60 that generates information indicating the estimated sensory characteristics of the subject based on the cerebral blood flow information acquired by the cerebral blood flow information acquisition unit and information on sensory characteristics associated with the cerebral blood flow information.

Description

Technical Field

[0001] The present invention relates to the generation of sensory characteristic information when a subject obtains a sensation about an object.

Background Art

[0002] In the purchase of bottled beverages, not only the taste of the contents but also the appearance of the container is one of the important factors, and containers are being developed that match the preferences of consumers and increase the willingness to purchase.

[0003] On the other hand, sensory evaluation, which shows the evaluation of a panel in multiple stages, has been known as one of the conventional evaluation methods, and this sensory evaluation is also used in the development of containers (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] One of the objectives of the present invention is to provide a novel technology for generating sensory characteristic information.

Means for Solving the Problems

[0006] The present inventor focused on the fact that changes can occur in cerebral blood flow when a subject obtains a sensation such as touch or vision about an object. As a result of intensive research, the present inventor found that there is a correlation between information on cerebral blood flow in a predetermined part of the brain and sensory characteristics. Furthermore, the present inventor found that it is possible to estimate the sensory characteristic information of a subject about an object by using the obtained information on the cerebral blood flow of the subject and information on the correlation between the information on cerebral blood flow and sensory characteristic information.

[0007] The gist of this invention is as follows: [1] A cerebral blood flow information acquisition unit acquires information on cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex, when the subject obtains sensations about an object. A sensory characteristics information generation system for an object, comprising: a sensory characteristics information generation unit that generates estimated sensory characteristics information for a subject based on information about the subject's cerebral blood flow acquired by the cerebral blood flow information acquisition unit and information about the correlation between the cerebral blood flow information and sensory characteristics information. [2] A sensory property information generation system according to [1], wherein the sensations a subject receives about an object are tactile and / or visual. [3] The functional property information generation system according to [1] or [2], wherein the cerebral blood flow information acquisition unit acquires information obtained from waveform information showing the temporal change in oxygenated hemoglobin concentration based on near-infrared spectroscopy as information related to cerebral blood flow. [4] The sensory characteristic information generation system according to [3], wherein the information obtained from the waveform information is one or more of the area under the curve of the waveform, the maximum value of oxygenated hemoglobin concentration over time, the mean value of oxygenated hemoglobin concentration over time, and regression coefficients using a general linear model. [5] A sensory property information generation system according to [1] or [2], wherein the object is a container. [6] A method for generating sensory characteristics information performed by a computer to generate estimated sensory characteristics information of a subject regarding an object, Information is obtained regarding cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex, when the subject obtains sensations about an object. A method for generating sensory characteristics information, which generates estimated sensory characteristics information of a subject based on acquired information on cerebral blood flow and information on the correlation between the cerebral blood flow information and sensory characteristics information. [7] A method for generating sensory property information according to [6], wherein the sensations that the subject obtains about the object are tactile and / or visual. [8] A method for generating functional characteristic information according to [6] or [7], wherein information is obtained from waveform information showing the temporal change in the amount of oxygenated hemoglobin based on near-infrared spectroscopy, as information related to cerebral blood flow. [9] The method for generating sensory characteristic information according to [8], wherein the information obtained from the waveform information is one or more of the area under the curve of the waveform, the maximum value of oxygenated hemoglobin concentration over time, the mean value of oxygenated hemoglobin concentration over time, and regression coefficients obtained using a general linear model.

[10] The method for generating sensory property information according to [6] or [7], wherein the object is a container.

[11] Computers, A cerebral blood flow information acquisition unit acquires information on cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex, when the subject obtains sensations about an object. A sensory characteristic information generation program that functions as a sensory characteristic information generation unit that generates estimated sensory characteristic information of a subject based on information about cerebral blood flow acquired by the cerebral blood flow information acquisition unit and information about the correlation between the cerebral blood flow information and sensory characteristic information.

[12] A sensory property information generation program as described in

[11] , wherein the sensations a subject receives about an object are tactile and / or visual.

[13] A functional property information generation program according to

[11] or

[12] , wherein the cerebral blood flow information acquisition unit acquires information obtained from waveform information showing the temporal change in oxygenated hemoglobin concentration based on near-infrared spectroscopy as information related to cerebral blood flow.

[14] The functional characteristic information generation program described in

[13] , wherein the information obtained from the waveform information is one or more of the area under the curve of the waveform, the maximum value of the oxyhemoglobin concentration within a period of time, the average value of the oxyhemoglobin concentration within a period of time, and the regression coefficient using a general linear model.

[15] The functional characteristic information generation program described in

[11] or

[12] , wherein the object is a container. [Advantages of the Invention]

[0008] According to the present invention, a novel technique for generating functional characteristic information can be provided. [Brief Description of the Drawings] [[ID=q14]]

[0009] [[ID=q17]] [Figure 1] It is a schematic diagram showing a location for measuring the cerebral blood flow of a subject based on near-infrared spectroscopy (NIRS) cerebral blood flow measurement. <000008q3> [Figure 2] It is a diagram showing an evaluation flow related to the measurement of the cerebral blood flow of a subject based on NIRS cerebral blood flow measurement and the execution of a sensory evaluation regarding palatability. [Figure 3] It is a graph showing the relationship between the measurement time and the oxyhemoglobin concentration (HbO) during measurement obtained by cerebral blood flow measurement. [Figure 4] It is a graph showing the relationship between the average value of the cerebral blood flow characteristic quantity and the average palatability score in the premotor area, the triangular part of the inferior frontal gyrus, and the dorsolateral part of the prefrontal cortex. [Figure 5] It is a graph showing the relationship between the average value of the cerebral blood flow characteristic quantity and the average palatability score. [Figure 6] It is a graph showing the relationship between the actual measured value of the sensory evaluation regarding palatability and the estimated value by cerebral blood flow measurement (regression model). [Figure 7] It is a diagram showing a configuration example of the functional characteristic information generation system according to the present embodiment. [Figure 8] [[ID=q4q]]It is a diagram showing a functional block of the functional characteristic information generation system according to the present embodiment. [Figure 9]This diagram shows the functional blocks related to the generation of sensory characteristic information in the sensory characteristic information generation system according to this embodiment. [Figure 10] This figure shows the processing flow related to the generation of sensory characteristic information in the sensory characteristic information generation system according to this embodiment. [Figure 11] This diagram shows the evaluation flow for measuring cerebral blood flow and performing sensory evaluation regarding novelty in cerebral blood flow measurement. [Figure 12] This graph shows the relationship between measured values ​​of sensory evaluation regarding novelty and estimated values ​​obtained from brain blood flow measurements (regression model). [Modes for carrying out the invention]

[0010] One embodiment of the present invention will be described in detail below.

[0011] Relationship between changes in cerebral blood flow and preferences First, we will explain the relationship between changes in brain blood flow when subjects perceive an object and the subjects' preferences. Figure 1 is a schematic diagram showing the brain regions where cerebral blood flow was measured in order to investigate the relationship between changes in cerebral blood flow based on near-infrared spectroscopy (NIRS) and the subjects' preferences. Figure 2 shows the evaluation flow chart for measuring cerebral blood flow in subjects using NIRS and performing sensory evaluation. NIRS is a non-invasive technique for measuring cerebral blood flow, allowing for real-time observation of changes in brain oxygen metabolism and blood volume. NIRS uses near-infrared light (wavelengths of 700-1000 nm), which has high penetration into living tissue, to analyze the absorption characteristics of light passing through brain tissue, enabling the measurement of oxygenated and / or deoxygenated hemoglobin concentrations.

[0012] A multi-channel NIRS system (FOIRE-3000, Shimadzu Corporation) was used to measure cerebral blood flow responses. The probes were positioned on the temporal region of each hemisphere, referencing the international 10-20 system. Each probe consisted of a 4x3 array with 6 emitters and 6 detectors, comprising 17 channels (Ch) in each hemisphere. The 3D coordinates of each probe were measured using a 3D digitizer (FASTRAK, Polhemus), and the 3D coordinates of the channels corresponding to each probe (all 34 Chs) were averaged across all participants. The positions of these channels (all 34 Chs) were rendered onto a standard brain at the Montreal Neuroscience Institute (MNI) using NIRS-SPM software. A summary of the rendered standard brain coordinate data is shown in Figure 1. The corresponding Brodmann area was estimated from the rendered standard brain coordinate data.

[0013] The study involved 32 subjects and used six types of PET bottles (PET bottle A (no label), PET bottle A (with label), PET bottle B (no label), PET bottle B (with label), PET bottle C (no label), PET bottle C (with label)). Furthermore, as shown in Figure 2, the time for measuring cerebral blood flow was set to 60 seconds (60s). After the measurement began, the subject held the PET bottle in their hand so that they could see it, looked at the entire container, and then released the PET bottle by putting it down. After the measurement was completed, the subjects were asked to perform a sensory evaluation of the PET bottle container on a 7-point scale. In this sensory evaluation, a higher numerical value indicated that the product was a better match for the subject's preference, as shown below. 1 point: I really dislike it. 2 points: Dislike 3 points: Somewhat dislike 4 points: Neither like nor dislike 5 points: I like it somewhat. 6 points: I like it. 7 points: I really like it.

[0014] Figure 3 is a graph showing the relationship between measurement time and oxygenated hemoglobin concentration during the measurement of cerebral blood flow in subjects using the NIRS method described above. By measuring cerebral blood flow using NIRS, information on oxygenated hemoglobin concentration can be obtained. Based on this information on oxygenated hemoglobin concentration and the measurement time, waveform information such as that shown in Figure 3, which illustrates the temporal change in oxygenated hemoglobin concentration, can be generated.

[0015] Figure 4 is a graph showing the relationship between the area under the curve (AUC), the average value of the oxygenated hemoglobin concentration (avg), the maximum value of the oxygenated hemoglobin concentration (max), or the average value of the regression coefficient (beta value) obtained using a general linear model (GLM), which can be obtained as a characteristic (cerebral blood flow characteristic) from waveform information showing the temporal change in oxygenated hemoglobin concentration, and the average value of the palatability evaluation score (average palatability score) obtained from sensory evaluation performed after the measurement of changes in cerebral blood flow. Figure 4 shows graphs for PET bottles (without labels) and PET bottles (with labels) used in the test. In this test, the area under the curve (AUC) was defined as the area where the oxygenated hemoglobin concentration was higher than 20% of the maximum value (max). Furthermore, for the beta value, a general linear model was used, and a linear equation was fitted to approximate the model function that occurs when an ideal change in oxygenated hemoglobin concentration occurs in accordance with the timing of the task, using the measurement data obtained from each channel. The more closely the measured data exhibits behavior that closely resembles the temporal evolution of the model function, the larger the absolute value of the beta value, which is the regression coefficient. Figure 4 shows that there is a correlation between cerebral blood flow characteristics (area under the curve (AUC), mean oxygenated hemoglobin concentration (avg), maximum oxygenated hemoglobin concentration (max), and regression coefficients (beta values) obtained using a general linear model) obtained by measuring cerebral blood flow in the premotor cortex, inferior frontal gyrus trigone, or dorsolateral prefrontal cortex, and sensory evaluation results regarding palatability. Figure 4 shows the results of analyzing measurement data from Ch9 on the right side corresponding to the premotor cortex, the results of analyzing measurement data from Ch13 and Ch17 on the right side corresponding to the inferior frontal gyrus trigone, and the results of analyzing measurement data from Ch28 on the left side corresponding to the dorsolateral prefrontal cortex. The measurement sites for each Ch are outlined in Figure 1.

[0016] Therefore, by repeatedly performing evaluations using the flow shown in Figure 2, for example, it is possible to construct information about the correlation between information on cerebral blood flow in the premotor cortex, inferior frontal gyrus trigone, or dorsolateral prefrontal cortex and sensory characteristic information, as shown in Figure 5. Figure 6 shows the estimated sensory evaluation results for palatability based on cerebral blood flow measurements of the PET bottles used in the test (unlabeled) and PET bottles (labeled), as well as the PLS regression model of the measured sensory evaluation results. The small difference between the estimated and measured values ​​demonstrates that cerebral blood flow measurement enables highly accurate evaluation.

[0017] The premotor cortex is a part of the cerebral cortex located in the frontal lobe, specifically in the anterior (parietal) part of the motor cortex, corresponding to Brodmann area 6 on the brain map. The premotor cortex is involved in planning, coordinating, and preparing for body movements. The inferior frontal gyrus trigone is located in the frontal lobe of the brain, specifically in the lower and posterior parts of the frontal lobe, just above the lateral sulcus (Sylvian sulcus), and corresponds to area 45 on Brodmann's brain map. The inferior frontal gyrus trigone is involved in language production, among other things. The dorsolateral prefrontal cortex is located in the frontal lobe of the brain and constitutes part of the prefrontal cortex. Specifically, it is located on the lateral and upper side of the frontal lobe, corresponding to the side of the forehead. In Brodmann's brain map, it corresponds to areas 9 and 46. The dorsolateral prefrontal cortex is involved in higher-order cognitive functions such as planning, decision-making, working memory, and attention control.

[0018] About the sensory characteristic information generation system of this embodiment This embodiment relates to a sensory characteristic information generation system for generating sensory characteristic information, which is information indicating the sensory characteristics of an object. Furthermore, the sensory characteristics of an object refer to the human evaluation of the object as a result of perceptions gained through the five human senses (sight, hearing, smell, taste, and touch). An example of a sensory characteristic of an object is the degree of human preference (liking) for that object. The object could be, for example, a plastic bottle.

[0019] Figure 7 is a schematic diagram of the sensory characteristics information generation system 100 of this embodiment. The sensory characteristics information generation system 100 of this embodiment includes an information processing device 10 having a processor 11 as an arithmetic processing device, a memory 12 as a main memory, and an SSD (Solid State Drive) 13 as an auxiliary storage device. Note that an HDD (Hard Disk Drive) can be used instead of an SSD, and the system is not particularly limited. The information processing device 10 also includes a network interface 14 for controlling communication with external units, a monitor 15, an input device 16 (keyboard, mouse, etc.), and a media reading device 17. Furthermore, the sensory characteristics information generation system 100 of this embodiment includes an information processing device 10 and a NIRS device 40 connected via a network NW.

[0020] Figure 8 is a functional block diagram relating to the sensory characteristics information generation system 100 of this embodiment. As shown in Figure 8, the sensory characteristics information generation system 100 consists of a display unit 20 that displays various information, an operation reception unit 22 that receives user input, a storage unit 24 that stores various information, a communication unit 26 connected to a network NW, and a control unit 30 that controls the operation of these units.

[0021] Specifically, the display unit 20 is composed of, for example, the monitor 15 shown in Figure 7, and has the function of displaying various information based on control signals from the control unit 30. Furthermore, as shown in Figure 7, the operation reception unit 22 is composed of an input device 16 such as a keyboard, mouse, or touch panel that also serves as the display unit 20, and has the function of receiving input operations from the user and the function of outputting information indicating the received input content to the control unit 30.

[0022] Furthermore, the storage unit 24 consists of a memory 12, an SSD 13, and an external server connected via a network, and has the function of writing and storing various types of information, as well as the function of reading various types of information. In this embodiment, the memory unit 24 stores a program for generating sensory characteristic information and information about the correlation between information on cerebral blood flow and sensory characteristic information used for estimating sensory characteristics (information for estimating sensory characteristics). The information for estimating sensory characteristics can be, for example, a graph showing the correlation between cerebral blood flow features such as the area under the curve of the waveform (AUC), the average value of oxygenated hemoglobin concentration (avg), the maximum value of oxygenated hemoglobin concentration (max), or the regression coefficient (beta value) obtained using a general linear model, as shown in Figure 5, and the average preference score.

[0023] Furthermore, the communication unit 26 is composed of network IF 14. Furthermore, the control unit 30 is composed of hardware such as the processor 11 and memory 12, and software such as a control program.

[0024] This control unit 30 has processing functions related to the exchange of various signals with the display unit 20, operation reception unit 22, storage unit 24, and communication unit 26, and a function to control the operation of each unit connected via a predetermined bus.

[0025] Figure 9 is a functional block diagram showing the case when the control unit 30 executes the sensory characteristic information generation program stored in the memory unit 24. In this embodiment, when a subject obtains sensations about an object such as a container, information on cerebral blood flow is obtained from one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex. Based on the obtained cerebral blood flow information and information for estimating sensory characteristics, estimated sensory characteristics information for the subject is generated. Furthermore, in this embodiment, the sensations that the subject experiences with the object can be tactile and visual.

[0026] The functional block diagram in Figure 9 will be explained in detail below. In this embodiment, the sensory characteristic information generation system 100 includes a cerebral blood flow information acquisition unit 50 and a sensory characteristic information generation unit 60. The cerebral blood flow information acquisition unit 50 also includes a waveform information generation unit 52 and a feature information acquisition unit 54.

[0027] The waveform information generation unit 52 generates waveform information from the measurement time and information on the oxygenated hemoglobin concentration of one or more brain regions of the subject, selected from the group consisting of the premotor cortex, inferior frontal gyrus trigone, and dorsolateral prefrontal cortex, which are acquired from the NIRS device 40.

[0028] The feature information acquisition unit 54 acquires cerebral blood flow features as information related to cerebral blood flow from the waveform information generated by the waveform information generation unit 52. Specifically, the feature information acquisition unit 54 acquires the area under the curve (AUC), the mean value of the oxygenated hemoglobin concentration (avg), the maximum value of the oxygenated hemoglobin concentration (max), or the regression coefficient (beta value) obtained using a general linear model as cerebral blood flow features from the waveform information. Of the above four types of cerebral blood flow features, the feature information acquisition unit 54 may acquire only one, or it may acquire two or more. When the area under the curve (AUC) is acquired, the area under the curve (AUC) can be appropriately set by a person skilled in the art, but for example, it can be the area of ​​the region where the oxygenated hemoglobin concentration is higher than 20% of the maximum value (max).

[0029] The sensory characteristic information generation unit 60 generates estimated sensory characteristic information of the subject based on the brain blood flow feature quantities acquired by the feature information acquisition unit 54 and the sensory characteristic estimation information stored in the memory unit 24. Specifically, an example of the generated sensory characteristic information is an evaluation value for the subject's estimated preferences.

[0030] Next, the processing flow for generating sensory characteristic information in this embodiment will be explained using Figure 10.

[0031] First, in step S101, upon receiving a user operation (start command) to execute the sensory characteristic information generation program, the control unit 30 executes the program to obtain information about the measurement time via the operation reception unit 22, and controls the NIRS device 40 to perform cerebral blood flow measurement of the subject, and obtains information from the NIRS device 40 about the oxygenated hemoglobin concentration of at least one of the following: the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex.

[0032] In step S102, the waveform information generation unit 52 generates waveform information based on information about the oxygenated hemoglobin concentration and the measurement time.

[0033] In step S103, the feature information acquisition unit 54 acquires cerebral blood flow features from the waveform information generated by the waveform information generation unit 52.

[0034] In step S104, the sensory characteristic information generation unit 60 generates estimated sensory characteristic information of the subject based on the brain blood flow feature quantities acquired by the feature information acquisition unit 54 and the sensory characteristic estimation information stored in the memory unit 24.

[0035] In step S105, the control unit 30 stores the generated estimated sensory characteristic information in the storage unit 24. In step S106, the control unit 30 displays the generated estimated sensory characteristic information on the display unit 20 and terminates the process.

[0036] Although this embodiment has been described above, the present invention is not limited thereto and can take other forms. For example, in the above embodiment, the subject receives sensations related to the object that are tactile and visual, but it may be either tactile or visual, or the subject may receive other sensations other than tactile and visual.

[0037] Furthermore, while information regarding the subject's preference (desire) for the subject is cited as sensory characteristic information, it is not limited to this. For example, novelty can also be cited as sensory characteristic information. Figure 11 shows the evaluation flow for measuring cerebral blood flow and performing sensory evaluation regarding novelty in cerebral blood flow measurement. Figure 12 shows the estimated results of sensory evaluation regarding the novelty of a PET bottle based on cerebral blood flow measurements in the premotor cortex, inferior frontal gyrus trigone, and dorsolateral prefrontal cortex, and the PLS regression model of the measured sensory evaluation results. Similar to the case of palatability, it is possible to construct information about the correlation between information on cerebral blood flow in the premotor cortex, inferior frontal gyrus trigone, or dorsolateral prefrontal cortex and sensory characteristic information by repeating the evaluation using the flow shown in Figure 11.

[0038] Furthermore, the object of the present invention is not particularly limited as long as it is an article with a shape, and examples include containers such as PET bottles, cans, and glass bottles used in the sensory evaluation above, as well as portable articles.

[0039] As described above, this embodiment provides a novel technology for generating sensory characteristic information. In this embodiment, sensory characteristic information such as the degree of preference for an object can be obtained without relying on the subject's declaration, making it possible to obtain more objective sensory characteristic information. [Explanation of symbols]

[0040] NW: Network, 11: Processor, 12: Memory, 13: SSD, 14: Network Interface, 15: Monitor, 16: Input Device, 17: Media Reader 20: Display unit, 22: Operation reception unit, 24: Storage unit, 26: Communication unit, 30: Control unit 40:NIRS device 50: Brain blood flow information acquisition unit, 52: Waveform information generation unit, 54: Feature information acquisition unit, 60: Sensory characteristic information generation unit 100: Sensory Characteristics Information Generation System

Claims

1. A cerebral blood flow information acquisition unit acquires information on cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex, when the subject obtains sensations about an object. A sensory characteristics information generation system for an object, comprising: a sensory characteristics information generation unit that generates estimated sensory characteristics information for a subject based on information about the subject's cerebral blood flow acquired by the cerebral blood flow information acquisition unit and information about the correlation between the cerebral blood flow information and sensory characteristics information.

2. The sensory characteristic information generation system according to claim 1, wherein the sensations obtained by the subject regarding the object are tactile and / or visual.

3. The functional property information generation system according to claim 1 or 2, wherein the cerebral blood flow information acquisition unit acquires information obtained from waveform information showing the temporal change in oxygenated hemoglobin concentration based on near-infrared spectroscopy as information related to cerebral blood flow.

4. The sensory characteristic information generation system according to claim 3, wherein the information obtained from the waveform information is one or more of the area under the curve of the waveform, the maximum value of oxygenated hemoglobin concentration over time, the average value of oxygenated hemoglobin concentration over time, and regression coefficients obtained using a general linear model.

5. The sensory property information generation system according to claim 1 or 2, wherein the object is a container.

6. A method for generating sensory characteristics information performed by a computer to generate estimated sensory characteristics information of a subject regarding an object, Information is obtained regarding cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex, when the subject obtains sensations about an object. A method for generating sensory characteristics information, which generates estimated sensory characteristics information of a subject based on acquired information on cerebral blood flow and information on the correlation between the cerebral blood flow information and sensory characteristics information.

7. The method for generating sensory characteristic information according to claim 6, wherein the sensations obtained by the subject regarding the object are tactile and / or visual.

8. A method for generating functional characteristic information according to claim 6 or 7, wherein information relating to cerebral blood flow is obtained from waveform information showing the temporal change in the amount of oxygenated hemoglobin based on near-infrared spectroscopy.

9. The method for generating functional characteristic information according to claim 8, wherein the information obtained from the waveform information is one or more of the area under the curve of the waveform, the maximum value of oxygenated hemoglobin concentration over time, the average value of oxygenated hemoglobin concentration over time, and the partial regression coefficient of the waveform.

10. The method for generating sensory property information according to claim 6 or 7, wherein the object is a container.

11. Computers, A cerebral blood flow information acquisition unit acquires information on cerebral blood flow in one or more brain regions selected from the group consisting of the premotor cortex, the inferior frontal gyrus trigone, and the dorsolateral prefrontal cortex, when the subject obtains sensations about an object. A sensory characteristic information generation program that functions as a sensory characteristic information generation unit that generates estimated sensory characteristic information of a subject based on information about cerebral blood flow acquired by the cerebral blood flow information acquisition unit and information about the correlation between the cerebral blood flow information and sensory characteristic information.

12. The sensory characteristics information generation program according to claim 11, wherein the sensations obtained by the subject regarding the object are tactile and / or visual.

13. The functional property information generation program according to claim 11 or 12, wherein the cerebral blood flow information acquisition unit acquires information obtained from waveform information showing the temporal change in oxygenated hemoglobin concentration based on near-infrared spectroscopy as information related to cerebral blood flow.

14. The functional property information generation program according to claim 13, wherein the information obtained from the waveform information is one or more of the area under the curve of the waveform, the maximum value of oxygenated hemoglobin concentration over time, the average value of oxygenated hemoglobin concentration over time, and the partial regression coefficient of the waveform.

15. A sensory property information generation program according to claim 11 or 12, wherein the object is a container.

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