TW202120904A - Food block forming device, chewing state evaluation method, texture evaluation method, and food block manufacturing method - Google Patents

Abstract

The present invention provides a food block forming device that can be used for texture evaluation of food by reproducing human chewing. A food block forming device 1 of the present invention includes: a lower artificial tooth 4 which is provided inside an artificial oral space S; an upper artificial tooth 5 which is disposed at a position opposite to the lower artificial tooth 4; an artificial tongue 6 which is disposed side by side with the lower artificial tooth 4 or the upper artificial tooth 5; an artificial cheek 7 which is wall-shaped and is disposed on a side of at least one of the lower artificial t00th 4 and the upper artificial tooth 5; and a robot arm 2a and a robot hand 2b which drive the lower artificial tooth 4 or the upper artificial tooth 5 to perform a biting movement. The food block forming device 1 chews food in the artificial oral space S by a biting action to form a food block.

Description

Food block forming device, chewing state evaluation method, taste evaluation method, and food block manufacturing method

The present invention relates to a food block forming device for chewing food in an artificial oral space and forming a food block, a mastication state evaluation method, a mouthfeel evaluation method, and a manufacturing method of a food block.

Conventionally, when evaluating the texture of food, the evaluator temporarily spit out the chewed food and evaluated it. In addition, in recent years, there is also known an evaluation system that uses a pressing mechanism and a pressure sensor to press the food to evaluate the taste.

For example, the taste evaluation system of Patent Document 1 is provided with: a pressing device for pressing a sample as an evaluation target of taste; a measuring device (pressure distribution sensor) for measuring the aforementioned sample when the sample is pressed The time-dependent change of the pressure distribution to which it is subjected; and, the taste evaluation means (control PC), which controls the pressing action of the pressing device, and evaluates the taste of the sample based on the pressure distribution data from the pressure distribution sensor.

This pressing device has a pair of upper and lower plates, a pressure distribution sensor is placed on the upper surface of the lower plate, and a sample is placed on the pressure distribution sensor. The upper board is arranged at a position opposite to the pressure distribution sensor in the up and down direction, and is connected with the linear slider. The linear slider drives the pressure sensor surface vertically in response to the pressing action control signal from the controlling PC, so the pressing action of the sample can be controlled (paragraphs 0022 to 0028, Fig. 1).

(Prior technical literature)

(Patent Document)

Patent Document 1: Japanese Patent No. 6324741

The taste evaluation system of Patent Document 1 is configured to evaluate the taste based on only the feature amount obtained from the temporal change of the pressure distribution. However, in fact, people's chewing actions are very personal differences in the way of bite and/or saliva infiltration, and it is difficult to accurately evaluate the taste.

The present invention has been developed in view of the above circumstances, and its object is to provide a piece-forming device that can reproduce human chewing and can be used to evaluate the taste of food.

In order to achieve the above-mentioned object, the food piece forming device of the present invention is provided with: a first artificial tooth, which is arranged in the artificial oral space; a second artificial tooth, which is arranged at a position opposite to the aforementioned first artificial tooth; and an artificial tongue, It is arranged side by side with the aforementioned first artificial tooth or the aforementioned second artificial tooth The front artificial cheek is wall-shaped and is arranged on the side of at least one of the first artificial tooth and the second artificial tooth; and, the driving means is to drive the first artificial tooth or the second artificial tooth The occlusal action is performed; wherein, the food arranged in the artificial oral space is chewed by the occlusal action to form the food piece of the food.

In the food piece forming device of the present invention, the first artificial tooth or the second artificial tooth in the artificial oral space is driven by a driving means, so that the first artificial tooth and the second artificial tooth bite into the food. The food piece forming device has an artificial tongue and artificial cheeks. As in the human mouth, the artificial cheeks become walls so that the bitten food is pushed back to the center of the artificial oral cavity, and the position of the food is adjusted by the artificial tongue. Thereby, the food pieces of the food are formed in the artificial oral cavity space, so the present invention can reproduce human chewing.

In the food piece forming device of the present invention, it is preferable that the aforementioned driving means performs an operation of moving one artificial tooth in a horizontal direction with respect to the other artificial tooth in addition to the aforementioned biting operation.

The driving means of the food piece forming device can move one artificial tooth (for example, the first artificial tooth) relative to the other artificial tooth (the second artificial tooth) in a horizontal direction. Thereby, the device can grind food on one side and form food pieces on the same side as in the human oral cavity.

In addition, in the food piece forming device of the present invention, it is preferable to include a food collecting means that collects the foods that have been separated due to the biting action to a predetermined position in the artificial oral space.

In the food piece forming device of the present invention, the food will be dispersed in the artificial oral cavity space due to the bite action. Therefore, food collection means are installed in the food block forming device to separate the discrete The food is collected at a predetermined position in the artificial oral space (for example, the upper surface of the artificial tongue). Thereby, the present invention can reproduce human chewing more faithfully and form food pieces.

In addition, in the food piece forming apparatus of the present invention, it is preferable to include a water supply means for supplying water to the food.

A water supply means is provided in the food piece forming device, thereby supplying water equivalent to saliva to the artificial oral cavity space. Thereby, this device can make use of water to easily make the food into lumps, which is close to the state of human chewing.

In addition, in the food piece forming device of the present invention, it is preferable to include: imaging means for photographing the food or the food pieces in the artificial oral space; and the evaluation means for photographing the food by the imaging means The image of the food piece evaluates the chewing state.

According to this configuration, the food or food pieces in the artificial oral space are photographed by the imaging means, and the evaluation means is used to evaluate the chewing state from the images by image analysis or the like. In this way, this device can quantitatively evaluate the degree of progress of the mastication state.

In addition, in the food piece forming device of the present invention, it is preferable that the aforementioned evaluation means evaluate the aforementioned food piece based on one or two selected from the group consisting of local changes and overall homogeneity.

The evaluation method of the food block forming device is to evaluate the food block in the artificial oral space based on one (one) or two (two) of local changes and overall homogeneity. In this way, the device can accurately evaluate the progress of the mastication state.

In addition, in the food piece forming device of the present invention, it is preferable to have: a machine learning method, which inputs images of food pieces with different chewing states and performs machine learning; wherein, the judgment method obtained by the aforementioned machine learning method is used to perform machine learning. Evaluate the aforementioned food pieces.

According to this structure, the machine learning method learns images of multiple pieces of food with different chewing states to establish a judgment method. In this way, this device allows the evaluation means to accurately evaluate the state of the food pieces.

The mastication state evaluation method of the present invention is a method for evaluating the mastication state of the aforementioned food using the food piece forming device described in any one of claims 1 to 7; the mouthfeel evaluation method of the present invention uses claims 1 to 7 7. The food piece forming device described in any one of 7, a method for evaluating the taste of the aforementioned food.

In addition, the mouthfeel method of the present invention is a method of manufacturing food pieces used in the food piece forming device according to any one of claims 1 to 4.

According to the present invention, various foods can be evaluated with high precision in their taste.

1: Food block forming device

2a: Robot arm

2b: Robot hand

3: Chewing Mechanism Department

4: Lower artificial teeth

5: Upper artificial teeth

6: Artificial tongue

7: Artificial cheeks

7’: Wall

8: Collect tongue

9: Camera

11: Frame

12: Water storage department

f: frequency

O: Origin

T: area

S: Artificial oral space

V _Ax : horizontal direction

V _Ay : vertical direction

V _By : vertical movement

S01~S08: steps

Fig. 1 is a schematic diagram illustrating the food piece forming device of the present invention.

Fig. 2 is a perspective view of the food piece forming device of the present invention.

Fig. 3 is a flow chart of the food block forming procedure performed by the food block forming device.

Fig. 4A is a diagram illustrating the chewing track of the food piece forming device.

Fig. 4B is a diagram illustrating five types of chewing orbits.

Fig. 5 is a diagram illustrating the food block forming experiment performed by the food block forming device.

Fig. 6A is a graph showing the result (contrast, Contrast) when the food piece forming device is used to evaluate the food.

Fig. 6B is a graph showing the result (Angular Second Moment) when food is evaluated by the food piece forming device.

Fig. 7A is a graph showing the result (normalized contrast) when food is evaluated by the food piece forming device.

Fig. 7B is a graph showing the result (the second moment of normalized angle) when food is evaluated by the food piece forming device.

Fig. 8A is a graph showing the results (standardized contrast) of two types of foods evaluated by the food piece forming device.

Fig. 8B is a graph showing the results of evaluating two types of foods (normalized angle second moment) with the food piece forming device.

Figure 9A is a diagram showing the results of evaluating two types of food with a Texture Analyser.

Fig. 9B is a graph showing the results of sensory evaluation of two types of foods.

(First implementation type)

Hereinafter, with reference to the drawings, the first embodiment of the food piece forming device of the present invention will be described.

First, referring to FIGS. 1 and 2, the outline of the food piece forming apparatus 1 of the present invention will be described.

FIG. 1 is a schematic diagram of the food piece forming apparatus 1. As shown in the figure, the food piece forming device 1 is mainly composed of a robot arm 2a, a robot hand 2b, and a chewing mechanism 3 that reproduces the human oral cavity. The robot arm 2a and the robot hand 2b correspond to the "driving means" of the present invention.

The front end of the robot arm 2a corresponds to the lower jaw, and lower artificial teeth 4 are installed. The motion system of the lower artificial tooth 4 has two degrees of freedom (V _Ax , V _Ay ), and can perform biting action (occlusal action) and mortar grinding action. In addition, the frame 11 made of aluminum corresponds to the upper jaw and is equipped with upper artificial teeth 5.

The biting action is an action of driving the robot arm 2a in the vertical direction (V _Ay ), whereby the lower artificial teeth 4 and the upper artificial teeth 5 bite the food. In addition. The grinding action is the action of driving the robot arm 2a in the horizontal direction (V _Ax ) to move and stagger the lower artificial teeth 4 and the upper artificial teeth 5 to grind food.

The lower artificial teeth 4 and the upper artificial teeth 5 are made of resin and are made by using a three-dimensional list machine. In addition, as shown in the figure, grooves and protrusions are formed in the central portions of the lower artificial teeth 4 and the upper artificial teeth 5, respectively.

An artificial tongue 6 is attached to the front end (movable part of the gripper) of the robot hand 2b. The movement of the artificial tongue 6 is only one degree of freedom of _{vertical movement (V By ).} The artificial tongue 6 is made of silicon resin, and an elastic sheet is attached to the surface of the artificial tongue 6 to expand and contract with the up and down movement of the artificial tongue 6.

In addition, an artificial cheek 7 is attached to a portion adjacent to the lower artificial tooth 4. The artificial cheek 7 is made of silicone, and the robot arm 2a performs the same action as the lower artificial tooth 4. The mastication mechanism part 3 has the above-mentioned various structures, and the food delivered to the artificial oral space is crushed and pulverized by mastication motion, mixed with saliva, and changed into a food piece.

Next, FIG. 2 shows an overall perspective view of the food piece forming device 1. As shown in the figure, a frame 11 is arranged above the mastication mechanism 3. The frame 11 is equipped with upper artificial teeth 5, in addition to the collection tongue 8 that scrapes and collects the chewed food (the "food collection means" of the present invention) and a camera (the "imaging means" of the present invention) ). A commercially available cotton swab is used as the collecting tongue 8 to scrape and gather the food scattered in the artificial oral space S due to the biting action, and move it to the upper surface of the lower artificial tooth 4 or the artificial tongue 6, for example.

In addition, it is preferable that the camera 9 is a web camera connected to a computer, and the camera 9 can automatically take pictures of the food being chewed. It will be stated in detail later that the image taken by the camera 9 is analyzed by a computer (the "evaluation means" of the present invention" to evaluate the food pieces (the degree of progress of chewing). With this, the food piece forming device 1 can quantify The chewing state of the food was evaluated sexually. In addition, the various steps of chewing, food collection, and image photography are automatically controlled by a computer program.

In addition, acrylic plates are used to make wall surfaces 7'on the side surfaces of the lower artificial teeth 4 and the artificial tongue 6, so as to prevent the chewed food from overflowing. Furthermore, in order to accurately reproduce the human oral cavity, a saliva supply unit ("moisture supply means" of the present invention) is required. In this embodiment, a spray is used to add water to the food block (0.6ml (ml) each time), but a water storage part 12 can also be provided in the upper artificial tooth 5 to supply water to the food block at every predetermined time. Thereby, the food scattered in the artificial oral space S is formed into small pieces due to moisture, which contributes to the formation of the food pieces. With the above-mentioned configuration, the food piece forming device 1 can faithfully reproduce human chewing in the artificial oral space S.

Next, referring to FIG. 3, the process of forming food pieces by the food piece forming apparatus 1 will be described with reference to a flowchart.

First, in the food piece forming apparatus 1, the counter i is set to "1", and the number of mastications n is set to "0" (step S01). In the food piece forming device 1, the lower jaw moves toward the fixed upper jaw, so the number of chewing cycles is also called the number of cycles of the lower jaw. After that, proceed to step S02.

In step S02, photography by the camera 9 is started. Specifically, the camera 9 photographs the chewing state of the food starting after that. After that, proceed to step S03.

Next, it is determined whether the counter i has reached the upper limit cycle number N (step S03). When it reaches the upper limit cycle number N, it progresses to step S08, and when it does not reach it, it progresses to step S04.

When the counter i has not reached the upper limit cycle number N (No in step S03), water supply is executed (step S04). This is the process of supplying the artificial oral cavity S with water instead of saliva. After that, proceed to step S05.

In step S05, chewing of food is performed. Here, the number of chewing times n will be increased by 5, so five consecutive jaw movements are performed. Before and after the fifth jaw movement, the artificial tongue 6 is moved up and down to stir the food pieces. Thereby, as the food is chewed in the artificial oral space S, food pieces are gradually formed. After that, proceed to step S06.

In step S06, the collection of food is executed. This is the process of making the collecting tongue 8 (cotton swab) pick up the food scattered in the artificial oral space S. After that, proceed to step S07.

In step S07, the counter i is incremented by 1, and the process returns to step S03. In addition, if the counter i has not reached the upper limit cycle number N (NO in step S03), the processing of steps S04 to S07 is repeated again.

On the other hand, when the counter i reaches the upper limit cycle number N (YES in step S03), the camera 9 stops shooting (step S08). After that, a series of food pieces are formed The processing of the program. As described above, the food piece forming apparatus 1 photographs each food and analyzes the state of the food piece formation (the degree of progress of mastication).

Next, referring to Figs. 4A and 4B, the masticatory trajectory of the food piece forming device 1 will be described.

In the food piece forming device 1 of the present invention, the orbit of the human jaw is linearized to give a parallelogram-shaped orbit. As shown in Fig. 4A, the occlusal position of the upper jaw teeth (upper artificial teeth 5) and the lower jaw teeth (lower artificial teeth 4) is set as the origin O, and the horizontal direction is the x-axis and the vertical direction is the y-axis. In addition, if the movement in the x-axis direction and the y-axis direction are expressed as a function at time t, the orbital system becomes the following Fourier series. In addition, f[Hz] is the frequency, X[mm] is the mortar grinding length, Y[mm] is the occlusal length, and α(0≦α≦2) is the parameter defining the ratio of the mortar abrasion to the occlusal length.

(1) When 0≦α<1

x(t)=αXA(t)‧‧‧(1A)

y(t)=YB(t)‧‧‧(1B)

(2) When 1≦α≦2

x(t)=XA(t)‧‧‧(2A)

y(t)=(2-α)YB(t)‧‧‧(2B)

among them,

Fig. 4B shows five types of (α=0, 0.5, 1.0, 1.5, 2.0) orbits that change the parameters, and the arrows show the direction of movement. In this embodiment, the food pieces (chewing state) when these various rails are used are observed.

Next, referring to Fig. 5, an experiment of the lumps formation by the lumps forming apparatus 1 will be described.

In this implementation type, the following are fixed as follows: upper limit cycle number N=6[times], frequency f=1.0[Hz], mortar grinding length X=10.0[mm], bite length Y=8.5[mm], and An experiment of forming food pieces by the food piece forming device 1 was performed. Using the sample food (A company’s doughnut, 5.0 g), each of the above-mentioned chewing orbits was tested ten times, and the number of chewing n=[0,5,10,15,20,25,30] was obtained. Food block image.

Figure 5 shows: from top to bottom, (a)α=0, (b)α=0.5, (c)α=1.0, (d)α=1.5, (e)α=2.0 and the situation of food Images corresponding to the number of chewings. As shown in the figure, as the number of chewing increases, the food pieces gradually cracked. In addition, it has also been observed that the way the food is broken up and the way it gathers is different with the chewing track.

Next, in order to quantitatively evaluate the difference between these food block images, the gray-level co-occurrence matrix (GLCM: Grey-Level Co-occurrence Matrix) is used for image texture analysis. Here, the gray-scale co-occurrence matrix refers to a matrix that represents the frequency of occurrence of pairs of pixels in a specified spatial relationship in an image (the derivation method is omitted).

The size of each food piece image in FIG. 5 is 1920×1080px, and a 224×224px part (area T) is cut out from it. In addition, the cut image is converted into a gray scale image and then the gray scale co-occurrence matrix is calculated, and f _C : contrast (local change) and f _A : second moment of angle (overall homogeneity) are calculated as the image Texture feature amount.

Contrast is to show the local change of the gray scale of the image, and the second angle is to show the homogeneity of the image.

Fig. 6A is a graph showing the contrast (local change) result of the above experiment. In this result, for comparison with the "artificial food block" formed by the food block forming device 1, it will contain the "human food" when a human (subject) chewed food (a doughnut from company A, 10.0g). Block" data (Human). In addition, the "human food piece" is the data of the subject's natural chewing with a metronome at a frequency of 1.0 [Hz].

In Fig. 6A, the horizontal axis represents the number of mastications n [times], and the vertical axis represents the local change f _C (average). f _C (average) uses the average value of all 10 runs, and is standardized with the value of the number of chewing n=0 [times]. From this result, it can be seen that especially when α=0.5 to 2.0 includes horizontal grinding motion, f _C (average) will increase once and then gradually decrease. The reason can be inferred that there will be parts of different nature in the early stage of chewing, but this part will gradually decrease as the mastication progresses.

In addition, (i), (ii), (iii) in Fig. 6A respectively show the number of chewing n=0, 10, 30 [times] in the case of α=1.0, and the corresponding food block image in Fig. 5 (Asterisk) You can also see the changes in food pieces caused by chewing. In comparison with the figure of "human food block", there will be _{a difference in the size of f C} (average), but it is shown that among the "artificial food blocks" formed by the food block forming device 1, α=1.0 is the closest to "human The tendency to eat lumps.

Fig. 6B is a graph showing the result of the second moment of angle (overall homogeneity) obtained from the above experiment. In Fig. 6B, the horizontal axis represents the number of mastications n [times], and the vertical axis represents the overall homogeneity f _A (average). f _A (average) is the average value of all 10 runs, and is standardized with the value of the number of chewing n=0 [times].

The tendency of the figure is based on the parameters close to the orbit of the biting motion (α=0, 0.5), the parameters close to the orbit of the mortar motion (α=1.5, 2.0), and the parameters belonging to the middle orbit (α=1.0), and Divided into three groups. When paying attention to the figure of "human food lump", f _A (average) will decrease until the number of chewing n=10 [times], and there will be a tendency of monotonous increase thereafter.

Among them, it also shows that α=1.0 in the "artificial food block" formed by the food block forming device 1 is close to the tendency of "human food block". From the above results, it is taught that the food lump forming device 1 of the present invention can reproduce human food lump by giving an appropriate chin rail.

In this embodiment, the contrast (local change) and the second angular moment (overall homogeneity) are extracted from the image taken by the camera 9 to evaluate the food mass (chewing state), but the contrast (local change) can also be used. And at least one of the second moment of angle (the overall homogeneity) to evaluate the food piece.

In addition, the camera image taken by the camera 9 can also be used for the machine learning model to judge and evaluate the food lump. Specifically, about 1,000 input images of the same food (doughnut) and different chewing states are prepared. Regarding the input image, images of food pieces corresponding to the number of chewing times (for example, 0 to 30 times) are taken, and these food pieces images are classified into classes according to the number of chewing times, and set as teacher data.

In addition, model learning of a convolutional neural network (CNN: Convolutional Neural Network) is performed to create an inferred model of the mastication category. In particular, in the convolutional neural network, the image system can be directly input with two-dimensional data, and can be automatically extracted during the learning process Effective feature quantity. In this way, when inputting a new image of food pieces, it is possible to easily and quickly determine how much the state of chewing the food pieces has progressed.

[Second Implementation Type]

Hereinafter, the second embodiment of the food piece forming device of the present invention will be described.

In the first embodiment, the food pieces obtained by the food piece forming apparatus 1 are photographed by the camera 9, and the food pieces are evaluated from the image analysis using contrast (local change) and the second moment of angle (overall homogeneity). The second embodiment is based on the same point of image analysis of food lumps, but uses improved evaluation values of "standardized contrast" and "standardized second moment of angle" to evaluate food lumps.

_{First, the definition of f C} (n) (average) of normalized contrast is explained. f _C (n) (average) is the average value of all 10 runs of contrast, subtracted from f _C (0) (average) (differential value), and then normalized by using the maximum absolute value of the difference value .

The f _C (n) (average) system can be obtained by the following formula.

_{Next, the definition of f A} (n) (average) of the standardized second moment of angle will be explained. f _A (n) (average) is the average value of all 10 runs of the second moment of the diagonal, minus f _A (0) (average) (differential value), and then use the maximum absolute value of the difference Standardized value.

The f _A (n) (average) system can be obtained by the following formula.

FIG. 7A is a graph showing the result of evaluating the contrast (local change) of food X (a donut of company A) using the food piece forming device 1. The parameters are close to human shape Cheng's "human food block" α=1.0. In addition, in formula (6), the case where the number of mastications n=m={0, 5, 10, 15, 20, 25, 30} is drawn and graphed.

In order to compare with the "artificial food block" (solid line) formed by the food block forming device 1, the data of the "human food block" is displayed by a dotted line. In addition, the "human food piece" is the data of the test subject's natural chewing with a metronome at a frequency of 1.0 [Hz].

This embodiment is approximately the same condition as α=1.0 in Fig. 6A. Therefore, a standardized local change f _C (n) (average) can be observed, which will first monotonically increase and the number of chewings n=10 to 20[ Times] become the largest, and then it will decrease. That is, parts of different properties appear in the early stage of chewing, and as the chewing progresses, this part will gradually decrease. The same goes for "human food".

FIG. 7B is a graph showing the second moment of angle (the overall homogeneity) when food X (a donut of company A) is evaluated by the food piece forming device 1. Among them, the parameter also adopts α=1.0 which is close to "human food block". Furthermore, in the formula (7), the case where the number of mastications n=m={0, 5, 10, 15, 20, 25, 30} is drawn and graphed (solid line).

It can be observed that f _A (n) (average) will increase monotonously first and become the smallest when the number of mastications n=10 to 15 [times], and then will increase little by little. That is, the homogeneity will immediately break down in the early stage of mastication, and as the mastication progresses, the homogeneity will gradually recover. The same goes for "human food" (dotted line). From the above results, it is taught that the food lump forming apparatus 1 of the present invention can reproduce human food lump even if the definition of local change and overall homogeneity is changed by giving an appropriate jaw track.

Next, with reference to Figs. 8A and 8B, the results of the investigation on whether the food piece forming device 1 can be used to evaluate foods with different tastes will be described.

In FIG. 8A, the solid line graph shows the result of the contrast (local change) when food X (a donut of company A) was evaluated by the food piece forming apparatus 1. In this implementation type, the parameter also adopts α=1.0 which is close to "human food mass". In addition, in formula (6), the case where the number of mastications n=m={0, 5, 10, 15, 20, 25, 30} is described.

The broken line graph shows the result of evaluating the contrast of the food Y (the doughnut of Company B) by the food piece forming apparatus 1. Since the parameter or the number of chewing times n (m) is set to be the same as that of the food X, as long as the waveforms of the two can be distinguished, the food piece forming device 1 can distinguish the taste of the food X and the food Y. Here, it can be observed that the chewing progress of food Y is faster than the chewing progress of food X.

In addition, in FIG. 8B, the solid-line graph shows the result of the second moment of angle (the overall homogeneity) when the food piece forming apparatus 1 evaluates the food X (a donut of company A). Here, the parameter also adopts α=1.0 which is close to "human food block". In addition, in formula (7), the case where the number of mastications n=m={0, 5, 10, 15, 20, 25, 30} is described.

The dotted graph shows the result of the second moment of the angle when the food piece forming device 1 is used to evaluate the food Y (the doughnut of Company B). As shown in the figure, it can be seen that the homogeneity of food Y recovers faster than that of food X, and the progress of chewing is faster.

Finally, referring to Figs. 9A and 9B, the results of the evaluation and sensory evaluation obtained by the texture analyzer of food X and food Y will be described.

Fig. 9A is a graph of food X and food Y evaluated by a texture analyzer (TA.XTplus: manufactured by Stable Micro Systems). In FIG. 9, the horizontal axis represents the number of mastications n [times], and the vertical axis represents the maximum stress [g] during compression.

Specifically, for food X and food Y, each of the food pieces chewed 5 to 30 times was measured by a texture analyzer, and the maximum stress [g] of the compressed food was measured. According to this, it is possible to obtain the result that the maximum stress of food Y is constantly smaller and softer than the maximum stress of food X.

Fig. 9B is a graph of sensory evaluation of food X and food Y. The sensory evaluation was conducted with five evaluators, and the chewing system was conducted with a metronome (set at 100 times/min). The evaluators are based on the VAS method and are evaluated on a scale of 0 to 10, and the average value of five evaluators repeated six evaluations is set as the sensory evaluation value.

According to this, through sensory evaluation, food Y can also obtain a score (melting sensation in the mouth) more than twice as high (P value shows a significant difference in the multiple comparison test. From the above results, it is verified that even if it is a donut, Food Y (Company B) also has a better melting feeling in the mouth. With the food block forming device 1 of the present invention, the taste of food X and food Y can be distinguished.

In this way, the food piece forming device 1 of the present invention can chew food and form food pieces in an artificial oral space S, such as a human oral cavity. In addition, by giving an appropriate chin rail to the food lump forming device 1, the steps of forming a human lump were successfully reproduced. By using the food piece forming device 1, for example, it is possible to investigate how a person chews a newly developed food.

In addition, by recognizing the image of the food pieces, the progress of chewing can be easily evaluated. Therefore, the food piece forming device 1 can also compare the texture of a plurality of foods. In addition, although a doughnut is used as the food of the present invention, the evaluation method is the same even for other foods. However, when evaluating the image of food pieces with a machine learning model, the image corresponding to the chewing state of the target food must be learned in advance.

3: Chewing Mechanism Department

4: Lower artificial teeth

5: Upper artificial teeth

6: Artificial tongue

7: Artificial cheeks

7’: Wall

8: Collect tongue

9: Camera

11: Frame

12: Water storage department

S: Artificial oral space

Claims (10)

A food piece forming device, which is equipped with: The first artificial tooth is set in the artificial oral cavity; The second artificial tooth is arranged at a position opposite to the aforementioned first artificial tooth; The artificial tongue is arranged side by side with the aforementioned first artificial tooth or the aforementioned second artificial tooth; The artificial cheek is wall-shaped and is arranged on the side of at least one of the first artificial tooth and the second artificial tooth; and The driving means is to drive the aforementioned first artificial tooth or the aforementioned second artificial tooth to carry out the occlusal action; wherein The food arranged in the artificial oral space is chewed by the biting action to form a block of the food. The food piece forming device according to claim 1, wherein the aforementioned driving means performs an operation of moving one artificial tooth in a horizontal direction with respect to the other artificial tooth in addition to the aforementioned biting operation. The food piece forming device according to claim 1 is provided with a food collecting means for collecting the food separated by the bite motion to a predetermined position in the artificial oral space. The food piece forming device described in claim 1 is provided with a water supply means for supplying water to the food. The food block forming device as described in claim 1, which is provided with: The imaging means is to photograph the aforementioned food or the aforementioned food pieces in the aforementioned artificial oral space; and The evaluation means is to evaluate the chewing state from the image of the food pieces taken by the imaging means. The device for forming food pieces according to claim 5, wherein the evaluation means evaluates the food pieces based on one or two selected from the group consisting of local changes and overall homogeneity. The food block forming device described in claim 5 is equipped with: a machine learning method, which inputs images of food blocks with different chewing states and performs machine learning; among them, The aforementioned food pieces are evaluated by the judgment method obtained by the aforementioned machine learning method. A method for evaluating the mastication state is to use the food piece forming device described in claim 1 to evaluate the mastication state of the aforementioned food. A method for evaluating the taste of the food is to use the device for forming pieces of food according to claim 1 to evaluate the taste of the aforementioned food. A method for manufacturing food pieces using the food piece forming device described in claim 1.

Images