Oral condition estimation device, oral condition estimation method, and oral condition estimation program

Abstract

To acquire information about the user's oral cavity using a simple method, classify the user's oral condition into a predetermined type, and provide care suggestions. [Solution] An oral condition classification device comprising: a self-check information acquisition unit that acquires self-check information obtained by a user self-checking the inside of their own mouth; and an oral condition estimation unit that estimates the user's oral condition based on the self-check information.

Description

Technical Field

[0001] The present invention relates to an oral condition estimation device, an oral condition estimation method, and an oral condition estimation program.

Background Art

[0002] In Patent Document 1, oral movement information obtained from a sensor device 21, function / state / care actual condition information such as occlusion state, chewing ability, mandibular movement ability, swallowing force, etc., and user information such as user attributes are analyzed to select and generate information on improvement proposals regarding the actual condition of the user's oral care (paragraphs

[0018] ,

[0047] to

[0048] , claim 1, etc. of the same document). Further, in Patent Document 2, information regarding oral secretions such as the saliva volume and viscosity of the user, information regarding the oral microbiota regarding the amount and types of bacteria present in saliva, etc., and the results of an interview with the user, etc., which are input using a user interface, are acquired, and these information are analyzed to output recommendation information regarding oral care (paragraphs

[0019] ,

[0040] , claim 1, etc. of the same document).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the technologies described in Patent Documents 1 and 2 above, in order to acquire and analyze information regarding the user's oral cavity, a predetermined instrument or the like must be used, and information on the oral cavity state could not be acquired by a simple method.

Means for Solving the Problems

[0005] To achieve the above objective, the oral cavity condition estimation device according to the present invention is A self-check information acquisition unit that acquires self-check information, which is information obtained when a user self-checks the inside of their own mouth, Based on the self-check information, the oral condition estimation unit estimates the user's oral condition, It is equipped.

[0006] Furthermore, in order to achieve the above objective, the oral condition classification method according to the present invention is The process involves a self-check information acquisition step, which involves obtaining self-check information obtained by the user performing a self-check of their own oral cavity, and Based on the self-check information, an oral condition estimation step is performed to estimate the oral condition of the user, This includes and is executed by an information processing device.

[0007] Furthermore, in order to achieve the above objective, the oral condition classification program according to the present invention is The process involves a self-check information acquisition step, which involves obtaining self-check information obtained by the user performing a self-check of their own oral cavity, and Based on the self-check information, an oral condition estimation step is performed to estimate the oral condition of the user, Have the computer execute it. [Effects of the Invention]

[0008] According to the present invention, information about the user's oral cavity can be obtained in a simple manner, the user's oral condition can be estimated, and further classification of the type and care suggestions can be made. [Brief explanation of the drawing]

[0009] [Figure 1] This is a diagram illustrating the general operation of the oral cavity state estimation device according to the first embodiment of the present invention. [Figure 2A] This is a block diagram illustrating the configuration of an oral cavity condition estimation device according to the first embodiment of the present invention. [Figure 2B]This figure shows the relationship between the score analyzed by the blood flow state estimation unit of the oral cavity state estimation device according to the first embodiment of the present invention and the blood flow index. [Figure 3] This is an example of a type classification table for an oral condition estimation device according to the first embodiment of the present invention. [Figure 4] This is a diagram illustrating the hardware configuration of an oral condition estimation device according to the first embodiment of the present invention. [Figure 5] This is a flowchart illustrating the processing procedure of the oral cavity condition estimation device according to the first embodiment of the present invention. [Figure 6A] This is a block diagram illustrating the configuration of an oral cavity condition estimation device according to a second embodiment of the present invention. [Figure 6B] This figure illustrates an example of the content presented by the presentation unit of the oral cavity state estimation device according to the second embodiment of the present invention. [Figure 7] This figure illustrates an example of a medical history table included in the oral condition estimation device according to a second embodiment of the present invention. [Figure 8] This is a diagram illustrating the hardware configuration of an oral condition estimation device according to a second embodiment of the present invention. [Figure 9] This is a flowchart illustrating the processing procedure of the oral cavity condition estimation device according to the second embodiment of the present invention. [Figure 10A] This is a block diagram illustrating the configuration of an oral cavity state estimation device according to a third embodiment of the present invention. [Figure 10B] This figure illustrates a method for deriving a predetermined type classified by the classification unit of the oral condition estimation device according to the third embodiment of the present invention. [Figure 10C] This is a dendrogram showing the results of a cluster analysis performed to derive a predetermined type classified by the classification unit of the oral condition estimation device according to the third embodiment of the present invention. [Figure 10D] This figure illustrates the first improvement proposal presented by the first presentation control unit of the oral cavity condition estimation device according to the third embodiment of the present invention. [Figure 10E]It is a diagram for explaining an example of a database referred to by a first presentation control unit and a second presentation control unit of an oral cavity state estimation device according to a third embodiment of the present invention. [Figure 10F] It is a diagram for explaining a second improvement plan presented by a second presentation control unit of an oral cavity state estimation device according to a third embodiment of the present invention. [Figure 11] It is a flowchart for explaining a processing procedure of an oral cavity state estimation device according to a third embodiment of the present invention. [Figure 12] It is a diagram for explaining an operation configuration of an oral cavity state estimation system according to a fourth embodiment of the present invention. [Figure 13A] It is a flowchart for explaining a procedure for acquiring blood flow information as self-check information in an oral cavity state estimation system according to a fourth embodiment of the present invention. [Figure 13B] It is a flowchart for explaining a procedure for measuring blood flow information in an oral cavity state estimation system according to a fourth embodiment of the present invention. [Figure 14] It is a flowchart for explaining a processing procedure in a user terminal in an oral cavity state estimation system according to a fourth embodiment of the present invention.

Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. However, the configurations, numerical values, processing flows, functional elements, etc. described in the following embodiments are merely examples, and modifications and changes thereof are free, and are not intended to limit the technical scope of the present invention to the following description.

[0011] [First Embodiment] An oral cavity state estimation device 100 according to a first embodiment of the present invention will be described with reference to FIGS. 1 to 5. FIG. 1 is a diagram for explaining an outline of the operation of the oral cavity state estimation device 100 according to the present embodiment. The oral cavity state estimation device 100 classifies the state inside a user's oral cavity based on the result of the user's self-check of the inside of his / her own oral cavity.

[0012] In this embodiment, a web application that runs on the internet is operated from a mobile device such as a smartphone owned by the user. Alternatively, the application may be installed on the user's smartphone, and the user may operate that application.

[0013] First, users access the website and follow the instructions displayed on their mobile device, such as a smartphone, to enter basic information such as their username, age, and gender. The entered username is used, for example, as a reference point when comparing information with past data. Age and gender are used to compare the user's oral health condition with that of people of the same gender and age group. Therefore, if a user does not wish to be compared with past data or with people of the same gender and age group, they can skip entering this information.

[0014] Next, the user checks their own oral cavity (self-check) according to the items displayed on the screens 110-112 of a mobile device such as a smartphone. Here, the information obtained through the self-check (self-check information) refers to objective evaluations (facts), not subjective evaluations based on the user's awareness or sensations that can be obtained through questionnaires or interviews.

[0015] The smartphone's display screens 110-112 sequentially display instructions to the user according to the items the user needs to check. First, the user checks the blood flow in their mouth according to the instructions on display screen 110. The blood flow check is performed by pressing and releasing the user's finger on their gums and observing the time it takes for the gums to return to their original color. After each check, the user performs an action such as tapping the selected item displayed on display screen 110, and the check results are recorded.

[0016] Next, the user performs a saliva check according to the display screen 111. The saliva check is performed by spitting saliva, which has been held in the mouth for a predetermined time, onto a tissue, and measuring the extent of the saliva's spread. When the user taps an option corresponding to the extent of the saliva's spread, the check result is recorded.

[0017] The user then checks the oral microbiome according to the display screen 112. The microbiome check is performed by cleaning the oral cavity with dental floss, interdental picks, or interdental brushes, and then examining the amount of deposits and odor attached to the dental floss, etc., after cleaning. The user taps on the appropriate selection item according to the condition of the deposits, etc., and the check results are recorded.

[0018] The results of the user's self-check, recorded in this manner, are sent to the oral condition estimation device 100. The oral condition estimation device 100 classifies the user's oral condition into a predetermined type, and the classification result is displayed on the display screen 120 of a smartphone or similar device. The display screen 120 shows "Weak Blood Circulation Type," which is displayed when the user's blood flow (blood circulation) is poor, but other factors such as saliva condition and bacterial flora are rated above the standard. For example, if the blood flow and saliva condition are rated below the standard, but the bacterial flora is rated above the standard, the user's oral condition will be displayed as "Weak Saliva and Blood Circulation Type." In this way, the user can find out which type their oral condition is classified into, and by looking at this, they can easily understand the weaker areas of their oral condition compared to others.

[0019] Next, the configuration of the oral condition estimation device 100 according to this embodiment will be described with reference to Figure 2A. The oral condition estimation device 100 has a self-check information acquisition unit 201, an oral condition estimation unit 202, and a classification unit 203. The oral condition estimation unit 202 further has a blood flow state estimation unit 221, a microbiota state estimation unit 222, and a saliva state estimation unit 223.

[0020] The self-check information acquisition unit 201 acquires self-check information, which is information obtained when the user self-checks the inside of their own mouth. Self-check information is information obtained when the user examines the condition of their own mouth themselves.

[0021] The self-check information acquisition unit 201 then acquires blood flow status information, microbiome status information, and saliva status information as self-check information. The blood flow status information is information about the time it takes for the gums to return to their original color when the user presses their gums with their finger and then releases their finger. When the user presses their gums with their finger, the color of the gums in the pressed area becomes whitish, and when the finger is released, it gradually returns to its original reddish color. The time it takes for the gums to return from white to red is considered the blood flow status information (display screen 110). The shorter the time it takes for the color to return to its original color, the better the blood flow condition of the user's gums is judged to be. This self-check information is obtained when the user performs a self-check as described below and inputs the results from their smartphone. In other words, in this embodiment, the self-check information acquisition unit 201 has the function of receiving self-check information transmitted from a smartphone.

[0022] The self-check of blood flow status is specifically performed by measuring the return of color when three locations on the gums are pressed with a finger. For each of the three locations, the user evaluates the blood flow status as follows: "returned quickly (approximately 1 second)" (score 2 points), "returned slowly (2 seconds or more)" (score 1 point), and "white area present" (score 0 points). The user then calculates the total score for the three locations, and this total score is acquired by the self-check information acquisition unit 201 as blood flow status information. For observing the gums during the self-check of blood flow status, it is preferable to display an image taken with a selfie camera and the second hand of a clock simultaneously on the smartphone screen. It is preferable to acquire the results of observation and measurement sequentially, rather than simultaneously for all three locations. As mentioned above, by actually touching their own gums, users can perceive their oral condition as something personal. Compared to measurements using photographs, questionnaires, or surveys, this method can improve their awareness of their own oral health and create a more reassuring experience.

[0023] The saliva status information (display screen 111) is based on the area covered by the saliva when the user spits saliva, which has been held in the mouth for a predetermined time (for example, 30 seconds), onto a designated piece of paper such as tissue paper. If the spread area is large, it is judged that the user has a large amount of saliva, and if the spread area is small, it is judged that the user has a small amount of saliva. The information based on the area is a rank of the area judged by the user visually using a coin as a reference, as shown in Figure 1. Instead of using a coin as a reference as described here, a mark indicating the area of ​​spread may be placed on the tissue paper or the like. Alternatively, when the camera of a smartphone is held over the tissue, an indication of the area of ​​spread may be displayed on the smartphone screen.

[0024] The microbiome status information (display screen 112) includes information such as the degree of soiling, odor, and blood contamination of the dental floss when the user uses dental floss to clean the interdental spaces of the back teeth, for example. Specifically, for the dental floss used to clean the back teeth, the microbiome status is evaluated by scoring three points according to their condition: (1) whether or not it is soiled, (2) whether or not it has an odor, and (3) whether or not it has blood on it. The self-check information acquisition unit 201 then acquires the microbiome status evaluated in this way as one of the self-check information items.

[0025] Furthermore, the self-check information acquisition unit 201 may acquire images or videos of the user's oral cavity in addition to the self-check information. The images of the oral cavity may be taken, for example, using the camera of a mobile device such as a smartphone owned by the user, or using another camera.

[0026] Furthermore, the evaluation methods for obtaining information about the oral cavity through self-checks are not limited to those described above. For example, these include the time it takes for a set amount of saliva to accumulate, visual evaluation of the tongue's color and the amount of plaque, evaluation of the color and plaque after running a cotton swab over the tongue three times, and evaluation of the roughness of the teeth by touching them with the tongue. In addition, these include evaluation of the color difference between the teeth and gums, evaluation of the viscosity of saliva by touching it with a finger, evaluation of the viscosity of saliva by the speed at which it falls from a specific height, evaluation of the turbidity of saliva, and evaluation of exhaled breath. In other words, the self-checks referred to in this specification are evaluations or measurements that are performed without using tools or instruments, or using only readily available everyday items and personal belongings.

[0027] The evaluation of exhaled breath can be performed, for example, by having the user breathe through their nose for 10 seconds with their mouth closed, exhale the accumulated breath into a plastic bag, close the bag, wait 10 seconds, and then smell the breath collected in the bag. The evaluation index in this case would be as follows: 0: no odor, 1: almost no odor, 2: slight odor, 3: easily noticeable odor, 4: strong odor, 5: very strong odor. However, any odor from the bag should be subtracted, and the evaluation should be conducted without brushing teeth after eating or drinking immediately prior to the evaluation.

[0028] The oral condition estimation unit 202 estimates the user's oral condition based on self-check information. The oral condition estimation unit 202 estimates the user's blood flow condition, microbiome condition, and saliva condition from blood flow condition information, microbiome condition information, and saliva condition information, and estimates the user's oral condition.

[0029] The blood flow state estimation unit 221 estimates the blood flow state of the user's gums from the blood flow state information. For example, as described above, the blood flow state estimation unit 221 scores the blood flow state information according to its state. The scoring method may be such that, for example, scores are assigned according to the time it takes for the gum color to return to normal, with higher (or lower) scores assigned the shorter the time it takes to return to normal.

[0030] Here, we will explain the evaluation of blood flow status with reference to Figure 2B. Ten healthy individuals (ages 20s to 60s) were scored using the method described above, and the relationship between these scores and gingival blood flow indicators measured by laser speckle flowgraphy was investigated. The relationship was examined using Graph 220 (ATI (Acceleration Time Index): time to reach peak) and Graph 230 (FAI (Flow Acceleration Index): explosive force that increases blood flow in a short period of time). In Graph 220, the horizontal axis is score (points) and the vertical axis is time, while in Graph 230, the horizontal axis is score (points) and the vertical axis is force.

[0031] The higher the total score (faster color recovery), the lower the ATI and the higher the FAI. Generally, ATI is known to increase with age, and FAI is known to decrease with age, so these indicators can be used to evaluate the blood flow status of the gums. From this, it can be seen that a "blood circulation score" can be calculated and evaluated based on the above score (7 levels from 0 to 6 points) as self-check information for blood flow status. The blood flow status estimation unit calculates the "blood circulation score" and evaluates a score of 3 or higher as "good blood flow" and a score of less than 3 as "insufficient blood flow".

[0032] The bacterial flora state estimation unit 222 estimates the bacterial flora state in the user's oral cavity from the bacterial flora state information. For example, the bacterial flora state estimation unit 222 scores the bacterial flora state information according to its state. The scoring method can be, for example, assigning scores according to the amount of dirt removed by dental floss, the strength of the odor, the amount of attached blood, etc., and lower (or higher) scores may be assigned to items with a large amount or a strong odor. In addition to using dental floss, the user may also determine the strength of the odor by smelling the breath exhaled into a plastic bag. In this embodiment, the sum of the score for the amount of dirt on the dental cloth, the score for the strength of the odor, and the score for the amount of attached blood is calculated, and if the score is above a predetermined score, it is evaluated as "insufficient bacterial flora," and if the score is below the predetermined score, it is evaluated as "good bacterial flora." The evaluation of the bacterial flora state is based on these scores and the bacterial composition ratio in paraffin gum chewing saliva obtained by analysis using 16srRNA-based Real-time PCR and next-generation sequencing. The bacterial composition ratios used as indicators were those of pathogenic bacteria and commensal bacteria, both of which have been reported to have a positive correlation with oral diseases such as bad breath, periodontal disease, and tooth decay. Examples of pathogenic bacteria include, but are not limited to, genera such as Porphyromonas, Tannerella, Treponema, Prevotella, and Veillonella. Examples of commensal bacteria include, but are not limited to, genera such as Streptococcus, Actinomyces, Neisseria, Rothia, and Haemophilus. Resting saliva, dental plaque, tongue coating, and gingival crevicular exudate may also be used to evaluate the bacterial flora. Evaluation methods may include bacterial count measurement using culture methods and shotgun metagenomic analysis.

[0033] The saliva state estimation unit 223 estimates the user's saliva state from saliva state information. For example, the saliva state estimation unit 223 can assign a score according to the area of ​​saliva spread. That is, an area larger than the size of a one-yen coin is evaluated as "a lot of saliva," and an area smaller than the size of a one-yen coin is evaluated as "a little saliva." The evaluation of saliva state is based on these scores and the actual amount of saliva produced during a 3-minute resting period. However, the saliva state can also be evaluated using other factors such as proteins or specific components in the saliva, and the saliva produced may also be evaluated using resting saliva or stimulated saliva.

[0034] Furthermore, the oral condition estimation unit 202 may estimate the user's oral condition by taking into account information obtained from acquired images or videos of the user's oral cavity in addition to the self-check information.

[0035] The classification unit 203 classifies the user's oral cavity into predetermined types based on the estimated oral condition. The classification unit 203 further classifies the user's oral cavity into predetermined types based on at least one of the estimated user's blood flow condition, microbiome condition, and saliva condition. The classification method by the classification unit 203 is performed according to (1) blood flow condition + microbiome condition, (2) blood flow condition + saliva condition, (3) microbiome condition + saliva condition, and (4) blood flow condition + microbiome condition + saliva condition. It is preferable for the classification unit 203 to classify the user's oral cavity into predetermined types based on at least two of the estimated user's blood flow condition, microbiome condition, and saliva condition. By creating prediction formulas with the scores of blood flow condition, microbiome condition, and saliva condition as the target variables, the condition can be predicted, and the type with the lowest score for each condition can be classified. For example, in the classification of (1) blood flow condition, if the blood flow condition score is low, it is the weak blood circulation type. (2) In the classification of the microbiome state, a low score for the microbiome state indicates a weak microbiome type. It is also possible to combine each state and classify them in relation to problems that the population of that state is prone to. For example, (4) In the classification of blood flow state + microbiome state, if both the blood flow state score and the microbiome state score are low, it indicates a gum trouble type, while if the blood flow state score is high and the microbiome state score is low, it indicates a bad breath trouble type. It is also possible to combine the medical history with the score of the state to determine whether the person is aware of the state and to classify them as a type with "hidden weak blood circulation". It is also possible to display the state directly as a score.

[0036] The types that can be classified include, but are not limited to, (a) weak blood flow type, (b) low saliva type, (c) weak bacterial flora type, (d) dental trouble type (saliva x weak bacterial flora), (e) gum trouble type (blood flow x weak bacterial flora), (f) dry mouth type (saliva x weak blood flow), (g) oral trouble type (saliva x bacterial flora x weak blood flow), and (h) hidden weak blood circulation type (weak blood circulation without awareness).

[0037] The classification unit 203 may classify the user's oral cavity condition into predetermined types based on each of the user's (1) blood flow condition, (2) microbiome condition, and (3) saliva condition. Even when each of the (1) to (3) conditions is used individually, it is possible to predict the condition by creating a prediction formula with the scores of blood flow condition, microbiome condition, and saliva condition as the target variables. In that case, it is possible to classify the type into categories such as weak blood circulation type, average blood circulation type, and good blood circulation type, or to display the condition score as is. Furthermore, by combining this with a medical interview, it becomes possible to perform more detailed classifications that are tailored to the user's oral health concerns and preferences.

[0038] Next, with reference to Figure 3, the type classification table 301 of the oral cavity state estimation device 100 will be described. The type classification table 301 stores states 312 in association with oral cavity types 311. Oral cavity types 311 are classifications of the user's oral cavity state by type. States 312 represent the estimated user's blood flow state, microbiome state, and saliva state for each type. The classification unit 203 then classifies the user's oral cavity state by referring to the type classification table 301. As can be seen from the figure, there are two types for each of the blood flow state, microbiome state, and saliva state. Furthermore, since there is no direct relationship between the three states, in this embodiment, it is possible to classify into eight types.

[0039] Referring to Figure 4, the hardware configuration of the oral condition estimation device 100 will be described. The CPU (Central Processing Unit) 410 is a processor for arithmetic control and realizes the various functional configurations of the oral condition estimation device 100 shown in Figure 2 by executing programs. The CPU 410 may have multiple processors and execute different programs, modules, tasks, threads, etc. in parallel. The ROM (Read Only Memory) 420 stores initial data, fixed data such as programs, and other programs. The network interface 430 communicates with other devices via the network. Note that the CPU 410 is not limited to one, and may have multiple CPUs, or may include a GPU (Graphics Processing Unit) for image processing. Furthermore, it is desirable that the network interface 430 has a CPU independent of the CPU 410 and write or read data to and from the RAM (Random Access Memory) 440 area. It is also desirable to provide a DMAC (Direct Memory Access Controller) for transferring data between the RAM 440 and the storage 450 (not shown). In addition, the CPU 410 recognizes that data has been received or transferred to the RAM 440 and processes the data. Furthermore, the CPU 410 prepares the processing results in the RAM 440, and leaves subsequent transmission or transfer to the network interface 430 or DMAC.

[0040] RAM440 is random access memory used by the CPU410 as a work area for temporary storage. RAM440 has a memory area reserved for storing the data necessary to realize this embodiment. Blood flow status data441 is data obtained by the user self-checking their own gums. Microbial flora status data442 is data obtained by the user self-checking using dental floss. Saliva status data443 is data obtained by the user self-checking the state of their own saliva. Estimated oral condition data444 is data about the user's oral condition estimated from the blood flow status, microbial flora status, and saliva status of the user's oral cavity self-checked by the user. Condition classification data445 is data about the user's oral condition classified from the estimated state of the user's oral cavity.

[0041] The transmitted and received data 446 is data transmitted and received via the network interface 430. The RAM 440 also has an application execution area 447 for running various application modules.

[0042] The storage 450 stores the database, various parameters, and the following data or programs necessary for realizing this embodiment. The storage 450 stores the type classification table 301. The type classification table 301 is a table that manages the relationship between oral type 311 and state 312, as shown in Figure 3.

[0043] The storage 450 further stores the self-check information acquisition module 451, the oral condition estimation module 452, and the classification module 456, which constitute the application program of this embodiment. The oral condition estimation module 452 further stores the blood flow condition estimation module 453, the microbiome condition estimation module 454, and the saliva condition estimation module 455.

[0044] The self-check information acquisition module 451 is a module that acquires self-check information obtained when a user self-checks their own oral cavity, and the aforementioned self-check information acquisition unit 201 is realized when the CPU 410 executes the self-check information acquisition module 451. The oral cavity state estimation module 452 is a module that estimates the user's oral cavity state based on the self-check information, and the aforementioned oral cavity state estimation unit 202 is realized when the CPU 410 executes the oral cavity state estimation module 452. As shown in Figure 4, the oral cavity state estimation module 452 includes a blood flow state estimation module 453, a microbiome state estimation module 454, and a saliva state estimation module 455. The blood flow state estimation module 453 is a module that estimates the blood flow state of the user's gums from blood flow state information, and the aforementioned blood flow state estimation unit 221 is realized when the CPU 410 executes the blood flow state estimation module 453. The microbiome state estimation module 454 is a module that estimates the microbiome state in the user's oral cavity from microbiome state information, and the aforementioned microbiome state estimation unit 222 is realized when the CPU 410 executes the microbiome state estimation module 454. The saliva state estimation module 455 is a module that estimates the state of the user's saliva from saliva state information, and the aforementioned saliva state estimation unit 223 is realized when the CPU 410 executes the saliva state estimation module 455. The classification module 456 is a module that classifies the state of the user's oral cavity into predetermined types based on the user's oral cavity state, and is a module that classifies the state of the user's oral cavity into predetermined types based on at least two of the estimated blood flow state, microbiome state, and saliva state. The aforementioned classification unit 203 is realized when the CPU 410 executes the classification module 456. These modules 451 to 456 are read into the application execution area 447 of RAM 440 by the CPU 410 and executed. The control program 457 is a program for controlling the entire oral cavity condition estimation device 100.

[0045] Next, the processing procedure of the oral condition estimation device 100 will be explained with reference to the flowchart shown in Figure 5. Each step shown in this flowchart is executed by the CPU 410 in Figure 4 using the RAM 440, realizing the functional configuration of the oral condition estimation device 100 shown in Figure 2.

[0046] In step S501, the self-check information acquisition unit 201 acquires self-check information obtained when the user self-checks their own oral cavity. In step S503, the blood flow state estimation unit 221 estimates the user's gum blood flow state from the acquired blood flow state information as self-check information. In step S505, the microbiome state estimation unit 222 estimates the microbiome state in the user's oral cavity from the microbiome state information as self-check information. In step S507, the saliva state estimation unit 223 estimates the user's saliva state from the acquired saliva state information as self-check information. In step S509, the classification unit 203 classifies the user's oral cavity state into a predetermined type based on at least two of the user's blood flow state, microbiome state, and saliva state.

[0047] According to this embodiment, the user's oral condition is classified using self-check information of their own oral cavity evaluated by the user, making it easy and convenient to classify the user's oral condition. By classifying the user's oral condition, it is possible to improve the user's awareness of oral care and their literacy regarding oral care products.

[0048] [Second Embodiment] Next, an oral condition estimation device according to a second embodiment of the present invention will be described using Figures 6A to 9. Figure 6A is a block diagram illustrating the configuration of the oral condition estimation device 600 according to this embodiment. The oral condition estimation device 600 according to this embodiment differs from the first embodiment in that it has a medical history information acquisition unit 601, a suggestion generation unit 602, and a presentation unit 603. Since the other configurations and operations are the same as in the first embodiment, the same reference numerals are used for the same configurations and operations, and their detailed explanations are omitted.

[0049] The medical information acquisition unit 601 acquires medical information, which is the user's response to a questionnaire about their oral condition. The content of the questionnaire to the user includes, for example, the number of times they brush their teeth per day, the time spent brushing, the amount of toothpaste used, the name of the toothpaste they are currently using, how they brush their teeth, and whether or not they use dental floss or interdental picks.

[0050] Furthermore, regarding toothpaste, you could ask about essential preferences such as (1) it doesn't foam much, (2) it foams well, (3) it has a weak cooling sensation, (4) it has a strong cooling sensation, or (5) it doesn't contain abrasives. Specifically, these items can be displayed side-by-side with checkboxes, and the user can check the items they believe apply to them. Other preferences could include, for example, whether it contains granules, whether the paste is soft, firm, or sticky, whether it has a minty flavor, a non-minty flavor, whether it contains high-concentration fluoride, whether it costs less than 500 yen, whether it costs more than 500 yen, whether it has a screw-on cap, whether it has a push-button cap, or whether it has a hinged cap.

[0051] For example, regarding mouthwash, you could ask about essential preferences such as (1) mild refreshing / irritating sensation, (2) strong refreshing / irritating sensation, or (3) alcohol-free. Furthermore, regarding toothbrushes, you could ask about essential preferences such as (1) small head, (2) large head, or (3) soft bristles.

[0052] Additionally, you could ask about the user's overall health and any oral health concerns. Regarding oral health concerns, you could ask which of the following apply to them: (1) bleeding gums, (2) bad breath, (3) sensitive teeth, (4) prone to cavities, (5) tooth discoloration, (6) dry mouth, (7) difficulty removing plaque, (8) receding gums, (9) food getting stuck between teeth, (10) a dirty tongue, or (11) prone to mouth ulcers. You could also ask about exercise habits, sleep duration, bathing habits, smoking, drinking, massage habits (gums, face), and eating habits (green tea, fermented foods, lean fish), or conduct a well-known stress check (e.g., are you stressed, are you prone to catching colds?).

[0053] The content of the above-mentioned questionnaire can be broadly categorized into the following areas: (A) basic information of the user, (B) preferences for oral care products, (C) oral health concerns, (D) lifestyle habits, (E) eating habits, and (F) overall health.

[0054] To elaborate further on these questions, (A) basic information includes (A-1) age, (A-2) gender, (A-3) the number of times you brush your teeth per day in the past month, (A-4) the approximate duration of brushing, (A-5) how you usually brush your teeth, (A-6) the brand of toothpaste you usually use, (A-7) the effects you expect from that toothpaste, (A-8) the amount of toothpaste you usually use, (A-9) the frequency of using interdental care tools (dental floss, interdental brushes, etc.) in the past month, (A-10) the frequency of gum massage (consciously stimulating the gums with a toothbrush, special tool, or finger) in the past month, and (A-11) the frequency of massages on other parts of the face in the past month. (B) In terms of preferences for oral care products, these include (B-1) essential points for toothpaste preference, (B-2) essential points for mouthwash preference, and (B-3) essential points for toothbrush preference.

[0055] (C) Regarding oral health concerns, we will conduct a medical interview by asking you to select the one option below that best describes the condition of your mouth over the past month. For example, (C-1) I have untreated cavities, (C-2) I am prone to cavities, (C-3) My teeth are sensitive (hypersensitivity), (C-4) My gums are swollen, (C-5) My gums are bleeding, (C-6) My gums are receding, (C-7) The color of my gums, (C-8) I have bad breath, (C-9) My teeth are discolored, (C-10) I have a lot of plaque, (C-11) I have a lot of tartar, (C-12) My teeth and The symptoms are selected from the following: (C-13) food getting stuck between teeth, (C-14) dry mouth, (C-15) misaligned teeth, (C-16) sticky mouth, (C-17) dirty tongue, (C-18) mouth ulcers, (C-19) clicking or pain in the joints when opening the mouth wide (temporomandibular joint disorder), (C-19) choking when eating, (C-20) ill-fitting dentures, (C-21) difficulty chewing hard foods, etc.

[0056] (D) Regarding lifestyle habits, the interview will be conducted by asking the patient to select the one option that best describes their lifestyle habits over the past month in terms of frequency. The options may include, for example, (D-1) exercise (including walking), (D-2) weekday sleep duration, (D-3) bathing in a bathtub (excluding showers only), (D-4) smoking, (D-5) drinking alcohol.

[0057] (E) Regarding eating habits, the interview will be conducted by asking the participant to select the option that best describes their eating habits over the past month in terms of frequency of consumption. The options include, for example, (E-1) snacks, (E-2) carbohydrates (rice, bread, noodles), (E-3) green and yellow vegetables, (E-4) mushrooms, (E-5) seaweed, (E-6) fermented foods (natto, yogurt, etc.), (E-7) dairy products (milk, cheese, yogurt, etc.), (E-8) sweets containing sugar, (E-9) citrus fruits, (E-10) meat, (E-11) fish, (E-12) lean fish (salmon, white fish, freshwater fish, bonito), (E-13) green tea, (E-14) coffee, black tea, etc.

[0058] (F) Regarding overall health, the interview will be conducted by asking the patient to select the one option that best describes their recent physical condition.The options are, for example, (F-1) My head feels heavy (I feel sluggish), (F-2) My eyes get tired (my eyes get tired more often than before), (F-3) I sometimes have a stuffy nose (my nose sometimes feels strange), (F-4) I sometimes feel dizzy (I never used to), (F-5) I sometimes feel lightheaded (I sometimes feel dizzy for a moment), (F-6) I sometimes have tinnitus (I never used to), (F-7) I often get canker sores (I get them more easily than before), (F-8) I have a sore throat (F-9) My tongue is often white (it used to be normal), (F-10) I no longer want to eat foods I used to like (my food preferences have changed), (F-11) Food feels heavy on my stomach (my stomach feels a bit off), (F-12) My stomach is bloated or painful (I alternate between diarrhea and constipation), (F-13) My shoulders are stiff, (F-14) My back and waist sometimes hurt (it didn't happen much before), (F-15) I can't seem to shake off fatigue (I get tired more easily than before), (F-16) I've lost weight recently (sometimes I lose my appetite), (F-17) I get tired easily when I do anything (I get tired more easily than before), (F-18) I sometimes can't wake up feeling refreshed in the morning (I feel like I'm still tired from the previous day), (F-19) I lack motivation for work, (F-20) I have trouble falling asleep (I can't fall asleep easily), (F-21) I dream a lot, (F-22) I wake up around 1 or 2 in the morning (and often I can't fall back asleep afterwards), (F- 23) Sometimes I feel suddenly breathless (like I don't have enough air), (F-24) I sometimes experience palpitations (which I didn't before), (F-25) My chest sometimes feels hot, (F-26) I catch colds often, (F-27) I get angry easily (I get irritated a lot), (F-28) My hands and feet are often cold (which I didn't used to do much), (F-29) I often sweat on my palms and underarms (I sweat more easily now), (F-30) I'm reluctant to meet people (which I didn't used to do so much), and so on.

[0059] The oral condition estimation unit 202 then estimates the user's oral condition based on the acquired questionnaire information and self-check information. Specifically, the oral condition estimation unit 202 estimates the user's oral condition by adding the questionnaire information to the self-check information, which includes blood flow status information, microbiome status information, and saliva status information. As one method of determining the oral condition using the questionnaire information and self-check information, the answers obtained from the questionnaire and the results of the self-check are each obtained as a stage evaluation, and these are converted into scores to be used as explanatory variables. Prediction formulas are then created with the scores of blood flow status, microbiome status, and saliva status as the dependent variables, making it possible to predict the condition. For example, the questionnaire information is not limited to dental problems such as "my gums are receding," but may also include questions about daily life, such as "I consume a lot of protein," as explanatory variables. These questions are asked on a 5-point scale, such as "applies," "somewhat applies," "neither agree nor disagree," "doesn't really apply," and "doesn't apply," and converted into a score from 1 to 5 points. As mentioned earlier, self-assessment information can also be converted into a score.

[0060] By adding subjective evaluations, such as those found in medical questionnaires, to self-assessment information, it becomes possible to calculate a score that more closely reflects the user's actual feelings, as subjective evaluations that users experience in their daily lives are added in addition to objective evaluations.

[0061] By adding explanatory variables other than self-checks and scoring the oral condition in this way, it becomes easier for users to confirm whether or not their blood flow (oral condition) has improved compared to past records.

[0062] One method for calculating a score for blood flow status (oral condition) is to use multiple regression analysis, with self-check information and questionnaire information as explanatory variables and the blood flow index (ATI, FAI) measured by Laser Speckle Flowgraphy as the dependent variable. In addition to multiple regression analysis, predictive models using machine learning techniques such as support vector machines (SVM), decision trees, neural networks, random forests, and naive Bayes can also be used.

[0063] The classification unit 203 then classifies the user's oral condition into a predetermined type based on the oral condition estimated by adding the medical interview information to the self-check information. The classification unit may also be configured to output a classification using only the self-check information. This allows for a comparison between the classification incorporating the medical interview information and the oral condition type using only the self-check information, providing the user with a stronger awareness of whether their perceived oral condition matches or differs from the actual condition. As one method of type classification, the classification can also be performed based on whether there is a discrepancy between the subjective symptom questionnaire results and the oral condition results. For example, a user who answers "I don't think so" to the questionnaire information "My gums are receding" is likely unaware that their blood flow is deteriorating. If the user's blood flow score is low, they can be classified as a "hidden weak blood circulation type," and the presentation unit 603 can display a message stating, "Your blood circulation is actually poor, so you need to be careful about gum recession," thereby increasing awareness of daily gum care. In this way, combining the results of self-reported symptoms with those of oral care can further raise awareness of oral care.

[0064] The suggestion generation unit 602 generates suggestions for the user regarding at least one of the oral care products and oral care methods to promote improvement in the user's oral condition, based on the classified type. Specifically, it prepares a database of suggestions for each type and searches the database for suggestions corresponding to the type. The suggestion generation unit 602 generates suggestions that match the type, such as the following: The suggestion generation unit 602 generates suggestions that include at least one of the following: oral care items (commercial or specialized products), oral care methods (brushing, interdental cleaning, tongue cleaning, gum massage, salivary gland massage, etc.), timing for performing oral care, time spent on oral care, lifestyle habits, eating habits, exercise habits, bathing habits, sleeping habits, smoking habits, drinking habits, etc.

[0065] The suggestion generation unit 602 generates one or more suggestions for oral care items from among toothpaste, mouthwash, toothbrush, interdental brush, and dental floss, according to the type.

[0066] The presentation unit 603 presents the classified types and the generated suggestions to the user. The presentation unit 603 may also present the types and suggestions to the user by displaying them on the screen of a mobile device such as a smartphone or tablet that the user possesses.

[0067] Alternatively, a graph 620 showing the user's oral condition (blood flow status) may be presented, for example, as shown in Figure 6B. If the user's age, gender, etc., have been obtained in advance, it is possible to visually display where the user's blood flow status stands compared to others of the same gender and age. This allows the user to confirm whether or not they need to improve the blood flow status of their gums, and can serve as an indicator for improving their oral care behavior in the future.

[0068] Furthermore, at the same time, the system may present suggestions from the suggestion generation unit 602 regarding oral care products and methods for improving blood flow. In this case, it is preferable that the suggestion generation unit 602 generates suggestions including what items can be improved, and the presentation unit 603 selects the suggestions to present according to the items to be improved. For example, the system may suggest dietary and lifestyle tips to the user. As a dietary tip, for example, vitamin E is said to have the effect of dilating peripheral blood vessels and improving blood flow, so a suggestion for bathing to enhance blood flow, including to the gums, could be made. In this way, by not only using self-check information to estimate the oral condition but also connecting it to care suggestions tailored to that condition, it is possible to not only increase the user's sense of personal responsibility for their oral condition but also to expect changes in their oral care behavior.

[0069] Furthermore, if the oral condition estimation device 600 has a storage unit that stores the estimation results of the user's past oral condition, it becomes possible to check how the user's oral condition has changed due to changes in their oral care by displaying the estimation results, for example, in a time-series graph. This makes it possible to visually confirm whether or not one's own care is causing changes in the actual oral condition.

[0070] Furthermore, the presentation unit 603 may also present potential oral health symptoms (such as swollen gums, discoloration, cavities, and tooth sensitivity) that the user should pay attention to in the future, based on the relationship between multiple oral health conditions and the user's actual oral health concerns, as "oral health concerns that your type is prone to." A database or trained model is prepared in advance and implemented in the oral health condition estimation device 100 so that potential oral health symptoms can be determined from the type and oral health concerns.

[0071] Next, with reference to Figure 7, the questionnaire table 701 of the oral condition estimation device 100 will be described. The questionnaire table 701 stores questionnaire content 712 in association with questionnaire items 711. The questionnaire items 711 are questionnaires to be asked of the user, classified according to their content. The questionnaire content 712 is the content of the questionnaire that is actually asked of the user. The questionnaire information acquisition unit 601 then acquires the user's answers to the questionnaire, which has been conducted by referring to the questionnaire table 701.

[0072] Referring to Figure 8, the hardware configuration of the oral condition estimation device 600 will be described. RAM 840 is a random access memory used by the CPU 410 as a work area for temporary storage. RAM 840 has a storage area reserved for storing the data necessary to realize this embodiment. Interview information data 841 is data that includes data on the content of the interview conducted with the user regarding the user's oral condition and data on the user's answers to the interview. Generated suggestion data 842 is data on suggestions generated according to the classified type.

[0073] The storage 850 stores the database, various parameters, and the following data or programs necessary for realizing this embodiment. The storage 850 stores the medical history table 701. The medical history table 701 is a table that manages the relationship between the medical history items 711 and the medical history content 712, as shown in Figure 7.

[0074] The storage 850 stores, in addition to the modules of Embodiment 1, a medical interview information acquisition module 851, a suggestion generation module 852, and a presentation module 853. The medical interview information acquisition module 851 is a module that acquires medical interview information regarding the user's answers to a medical interview about the user's oral condition, and is implemented by the CPU 410, thereby realizing the medical interview information acquisition unit 601. The suggestion generation module 852 is a module that generates suggestions to the user about at least one of the oral care products and oral care methods to promote improvement of the user's oral condition, based on the classified type, and is implemented by the CPU 410, thereby realizing the suggestion generation unit 602. The presentation module 853 is a module that presents the classified type and the generated suggestions to the user, and is implemented by the CPU 410, thereby realizing the presentation unit 603. These modules 851 to 853, like the modules described in Embodiment 1, are read into the application execution area 447 of the RAM 840 by the CPU 410 and executed.

[0075] Next, the processing procedure of the oral condition estimation device 600 will be explained with reference to the flowchart shown in Figure 9. Each step shown in this flowchart is executed by the CPU 410 in Figure 8 using the RAM 840, realizing the functional configuration of the oral condition estimation device 600 shown in Figure 6.

[0076] In step S901, the medical information acquisition unit 601 acquires medical information regarding the user's responses to a medical questionnaire about their oral condition. In step S903, the suggestion generation unit 602 generates suggestions for the user, based on the classified type, regarding at least one of the oral care products and oral care methods to promote improvement of the user's oral condition. In step S905, the presentation unit 603 presents the classified type and the generated suggestions to the user.

[0077] According to this embodiment, the user's oral condition can be visualized, thereby improving the user's awareness of oral care and literacy regarding oral care products. Furthermore, by adding other oral conditions such as the state of the bacterial flora and saliva in addition to the blood flow state, the user's awareness of their oral condition can be further enhanced. The user can improve their own oral condition by performing oral care according to the presented suggestions.

[0078] [Third Embodiment] Next, an oral condition estimation device according to a third embodiment of the present invention will be described using Figures 10A to 11. Figure 10A is a block diagram illustrating the configuration of the oral condition estimation device 1000 according to this embodiment. The oral condition estimation device 1000 according to this embodiment differs from the first embodiment in that it has a classification unit 1001, a first presentation control unit 1002, and a second presentation control unit 1003. Since the other configurations and operations are the same as in the first embodiment, the same reference numerals are used for the same configurations and operations, and their detailed explanations are omitted.

[0079] The oral cavity condition estimation device 1000 includes a classification unit 1001, a first presentation control unit 1002, and a second presentation control unit 1003.

[0080] The classification unit 1001 classifies the user's oral condition into a predetermined type based on the estimated user's oral condition. In this embodiment, the predetermined type is derived by analyzing parameters indicating the oral condition of multiple people, along with information on the lifestyle habits of multiple people. Parameters indicating the oral condition include, for example, the amount of plaque, the protein and fluoride concentrations in plaque, calcium concentration, the amount of tartar, the amount of bleeding, recession, the amount and ratio of specific bacteria, parameters related to blood flow and blood flow in the gums, the amount of saliva, the salivary protein concentration, the color and brightness of the teeth, the bad breath index, dryness of the oral cavity, dryness of the tongue, the depth of the periodontal pocket, the degree of inflammation, and the presence or absence of cavities. Information regarding lifestyle habits includes, for example, the frequency of bathing, whether or not mouthwash is used, the number and duration of brushing teeth, the method of brushing teeth (horizontal scrubbing type, vertical scrubbing type, etc.), the frequency of fluid intake, the timing and frequency of meals, the frequency of smoking, the amount and frequency of alcohol consumption, the amount and frequency of intake of protein, carbohydrates, fruits, vegetables, fats, salty foods, etc., and the amount of sleep.

[0081] The derivation method for a predetermined type will be explained with reference to Figure 10B. In this embodiment, 135 healthy individuals (ages 20-60) were used as the population 1011 for analyzing information on parameters and lifestyle habits. First, factor analysis was performed on the parameters and lifestyle habits indicating oral condition in the population 1011. As a result of the factor analysis, nine factors 1021 (F1-F9) were obtained. The nine factors 1021 (F1-F9) were related to blood flow, blood flow disturbance, plaque / gingivitis, saliva strength, saliva cleanliness, saliva volume, bad breath, tooth color, and periodontitis / regression, respectively. Then, the population 1011 was subjected to cluster analysis using hierarchical clustering based on the similarity of the obtained nine factors 1021.

[0082] The cluster analysis method will be explained with reference to Figure 10C. In dendrogram 1040, the horizontal axis represents the sample ID (Identifier) ​​of each data sample (each of the 135 individuals used in the population 1011), and the vertical axis represents the distance (Euclidean distance) at which clusters are merged. In other words, it visualizes the mechanism by which data samples with high similarity (short Euclidean distance) are merged into clusters among the 135 data. In dendrogram 1040, a dividing line was placed at the position indicated by the sign L, dividing the data into nine clusters 1041 to 1049. The dividing line L was placed at a position where the number of derived clusters was neither too many nor too few.

[0083] Of the nine clusters 1041 to 1049, clusters 1041 and 1042 each have only one member. Cluster 1041 has a significantly higher score for factor F4 (saliva strength) compared to the other clusters, and cluster 1042 has a significantly higher score for factor F5 (saliva cleanliness) compared to the other clusters. Therefore, the one member in cluster 1041 and the one member in cluster 1042 are considered outliers, and all seven clusters from 1043 to 1049 are designated as the predetermined type 1031 in this embodiment.

[0084] The characteristics of each of the seven predetermined types 1031 are shown below. <Concerned about tooth discoloration, slightly weaker saliva type (CL1)> The teeth are discolored and there is gum recession. There is no plaque or inflammation. The quality of the saliva is slightly poor. <<Type Characteristics>> • Blood flow volume: Slightly poor • Blood flow quality: Good Plaque and inflammation: Fairly good • Saliva strength: Slightly weak • Saliva cleanliness: Poor • Saliva volume: Normal • Bad breath: Normal • Tooth color: Bad • Gum recession: Slightly present

[0085] <For those concerned about receding gums and weak saliva production (CL2)> The gum recession is particularly significant. The quality of saliva is somewhat poor. Plaque and gingivitis are not a problem. <<Type Characteristics>> • Blood flow volume: Normal • Blood flow quality: Normal Plaque and inflammation: Fairly good • Saliva strength: Slightly weak • Saliva cleanliness: Average • Saliva volume: Slightly low • Bad breath: Normal • Tooth color: Normal • Gum recession: Yes

[0086] <Type with concerns about plaque and weak blood circulation (CL3)> Poor blood flow in both quantity and quality. Low saliva production. <<Type Characteristics>> • Blood flow volume: Poor • Blood flow quality: Poor • Plaque and inflammation: Normal • Saliva strength: moderately strong • Saliva cleanliness: Good • Saliva volume: Slightly low • Bad breath: Normal • Tooth color: Normal • Gum recession: Normal

[0087] <Type with enhanced oral potential (CL4)> There are no problems with saliva quality, tooth color, or gum recession. However, there is plaque and gingivitis. <<Type Characteristics>> • Blood flow volume: Normal • Blood flow quality: Fairly good • Plaque and inflammation: Slightly bad • Saliva strength: Strong • Saliva cleanliness: Average • Amount of saliva: Slightly high • Bad breath: Normal • Tooth color: Fairly good • Gum recession: None

[0088] <Types who are concerned about saliva and their mouth (CL5)> The teeth are a good color. The quantity and quality of saliva are poor. There is plaque and gingivitis. <<Type Characteristics>> • Blood flow volume: Normal • Blood flow quality: Fairly good • Plaque and inflammation: Slightly bad • Saliva strength: Slightly weak • Saliva cleanliness: Good • Amount of saliva: Low • Bad breath: Good • Tooth color: Good • Gum recession: None

[0089] <Type concerned with blood circulation and saliva quality (CL6)> Blood flow is good. The gums are healthy, but the quality of blood flow and saliva is poor. <<Type Characteristics>> • Blood flow volume: Good • Blood flow quality: Poor • Plaque and inflammation: Bad • Saliva strength: Slightly weak • Saliva cleanliness: Poor • Saliva volume: Normal • Bad breath: Slightly bad • Tooth color: Normal • Gum recession: None

[0090] <For those concerned about receding gums and weak blood circulation (CL7)> You have a lot of saliva, so plaque doesn't easily accumulate. However, there are problems with blood flow quality and gum recession. <<Type Characteristics>> • Blood flow volume: Normal • Blood flow quality: Poor • Plaque and inflammation: Good • Saliva strength: Normal • Saliva cleanliness: Average • Amount of saliva: High • Bad breath: Slightly bad • Tooth color: Normal • Gum recession: Normal

[0091] The classification unit 1001 classifies the user's oral condition into a predetermined type 1031 derived by the method described above, based on the oral condition estimated by the oral condition estimation unit 202.

[0092] The first presentation control unit 1002 presents the user with a predetermined classified type and allows the user to select from two improvement proposals 1051 and 1052 (first improvement proposals) corresponding to the predetermined type. The first presentation control unit 1002 may also present the user with the type and improvement proposals 1051 and 1052 by displaying them on the screen of a mobile device such as a smartphone or tablet held by the user.

[0093] Referring to Figure 10D, improvement suggestions 1051 and 1052 will be explained using the example of a case where the classified predetermined type is <Type with plaque concerns and weak blood circulation (CL3)>. In this case, there is room for improvement in the amount of plaque and the amount of blood flow. Therefore, improvement suggestions 1051 and 1052 include "I want to remove plaque" and "I want to improve blood circulation." Thus, improvement suggestions 1051 and 1052 are general improvement suggestions for each predetermined type. Improvement suggestions 1051 and 1052 can be retrieved, for example, by searching a database that records the first improvement suggestion for each type.

[0094] The user selects at least one of the following improvement suggestions: 1051 ("I want to remove plaque") and 1052 ("I want to improve blood circulation"). For example, if the user feels the need to remove plaque, or is interested in reducing the amount of plaque, they select improvement suggestion 1051. If the user feels the need to improve blood circulation, or is interested in improving blood circulation, they select improvement suggestion 1052. Furthermore, if the user feels both the need to remove plaque and improve blood circulation, or is interested in both reducing the amount of plaque and improving blood circulation, they select both improvement suggestions 1051 and 1052. The first presentation control unit 1002 may present three or more improvement suggestions. In addition, instead of presenting multiple improvement suggestions 1051 and 1052 side by side, they may be presented one by one in sequence.

[0095] The second presentation control unit 1003 generates improvement proposals 1061 to 1064 (second improvement proposals) for at least one of the oral care products and lifestyle improvement proposals to promote improvement in the user's oral condition, based on the classified predetermined type and the improvement proposals 1051 and 1052 selected by the user, and presents the generated improvement proposals 1061 to 1064 to the user. Improvement proposals 1061 to 1064 are specific means for realizing improvement proposals 1051 and 1052. The generation of improvement proposals 1061 to 1064 is performed based on a database created using the population 1011 used to derive the predetermined type 1031. The database stores the oral care products and lifestyle habits used in association with each type in the population 1011.

[0096] Figure 10E shows an example of a database. Database 1070 stores information on the data samples used for cluster analysis. Specifically, for each data sample, it stores the cluster to which the sample belongs; nine factor scores; lifestyle habits including the number of times teeth are brushed, the frequency of bathing, and the amount of vegetables consumed; and information on the use of oral care products. The second presentation control unit 1003 generates improvement suggestions based on this information.

[0097] Refer to Figures 10E and 10F to explain improvement suggestions 1061-1064. For example, suppose a user presented with improvement suggestions 1051 and 1052 selects improvement suggestion 1051 ("I want to remove plaque"). In this case, the second presentation control unit 1003 searches the database 1070 for items that differ between people with a lot of plaque and those with little plaque, among those classified as <Plaque-concerned, poor blood circulation type (CL3)>. Specifically, since the factor 3 (F3) score corresponds to the amount of plaque, it extracts data samples of the Plaque-concerned, poor blood circulation type (CL3) and searches for items that differ between people with high and low scores in the "oral care products" and "lifestyle" categories. For example, the search of database 1070 might reveal that people with little plaque, compared to those with a lot of plaque, differ particularly in their use of "plaque-removing toothbrushes" as an oral care product and in their lifestyle habits in "eating a lot of vegetables at dinner." In this case, the second presentation control unit 1003 generates improvement suggestion 1061 ("plaque-removing toothbrush") for oral care products and improvement suggestion 1062 ("increase the amount of vegetables in dinner") for lifestyle improvement suggestions.

[0098] Furthermore, suppose a user who was presented with improvement suggestions 1051 and 1052 selected improvement suggestion 1052 ("I want to improve my blood circulation"). In this case, the second presentation control unit 1003 searches the database 1070 for items that differ between people with high blood flow and those with low blood flow among people classified as <Plaque-concerned, weak blood circulation type (CL3)>. For example, suppose the database search reveals that people with high blood flow use "toothpaste that improves blood circulation" as an oral care product and have a lifestyle habit of "bathing frequently". In this case, the second presentation control unit 1003 generates improvement suggestion 1063 ("toothpaste that improves blood circulation") for oral care products and improvement suggestion 1064 ("increase bathing frequency") for lifestyle habit improvements.

[0099] The second presentation control unit 1003 presents the classified type and the generated improvement suggestions 1061 to 1064 to the user. Specifically, it presents the type and improvement suggestions 1061 to 1064 to the user by displaying them on the display screen of a mobile device such as a smartphone or tablet.

[0100] In this embodiment, information on the lifestyle habits of multiple individuals is taken into account when deriving a predetermined type 1031. However, instead, the predetermined type 1031 may be derived by analyzing parameters indicating the oral condition of multiple individuals without taking such information into account. Furthermore, non-hierarchical clustering may be used instead of hierarchical clustering as the cluster analysis method. Moreover, cluster analysis may be performed on the population 1011 based on parameters indicating oral condition and information on lifestyle habits without performing factor analysis. When performing cluster analysis without factor analysis, parameters indicating oral condition, such as tooth color, amount of plaque, amount of blood flow, and quality of blood flow, can be stored in the database 1070 instead of factor scores as indicators to be referenced when generating improvement proposals 1051, 1052, 1061-1064, thereby enabling the presentation of improvement proposals using the same method as described above. Furthermore, grouping methods other than cluster analysis, such as k-means, principal component analysis, and self-organizing maps, may be used in addition to cluster analysis.

[0101] Next, the processing procedure of the oral condition estimation device 1000 will be explained with reference to the flowchart shown in Figure 11.

[0102] In step S1101, the classification unit 1001 classifies the user's oral condition into a predetermined type 1031. In step S1103, the first presentation control unit 1002 presents the classified predetermined type 1031 and also presents selectable improvement suggestions 1051 and 1052 corresponding to the predetermined type 1031. The user, upon being presented with improvement suggestions 1051 and 1052, selects at least one of the presented improvement suggestions 1051 and 1052. In step S1105, the second presentation control unit 1003 generates and presents improvement suggestions 1061 to 1064 to promote improvement of the user's oral condition, based on the classified predetermined type 1031 and the improvement suggestions 1051 and 1052 selected by the user.

[0103] According to the oral condition estimation device 1000 of this embodiment, the user's oral condition can be classified into a predetermined type 1031 derived by analyzing the population 1011, thereby enabling more accurate classification of the user's oral condition. Furthermore, since the device presents improvement plans 1061 to 1064 corresponding to the improvement plans 1051 and 1052 selected by the user, the user can implement the improvement plans 1061 to 1064 with greater confidence. Moreover, the oral condition estimation device 1000 can present not only oral care products but also lifestyle improvement plans as improvement plans 1061 to 1064 to the user, thereby promoting lifestyle improvements from a broader perspective that includes the user's lifestyle habits.

[0104] Furthermore, in this embodiment, as described above, there are multiple first improvement proposals 1051 and 1052, and second improvement proposals 1061 to 1064 are generated and presented according to the first improvement proposal 1051 and 1052 selected by the user.

[0105] In contrast, if there is only one first improvement plan, the first presentation control unit 1002 presents that first improvement plan, and a second improvement plan is generated and presented in accordance with that first improvement plan. Specifically, the first presentation control unit 1002 presents the only first improvement plan, and the second presentation control unit 1003 generates and presents a second improvement plan in accordance with that first improvement plan. For example, in the initial stages when a user begins using the oral condition estimation device 1000, there are multiple areas in the user's oral condition that need improvement. Therefore, in the initial stages, multiple first improvement plans are presented for selection. Subsequently, as the user implements the second improvement plans presented by the oral condition estimation device 1000 and the user's oral condition improves, the number of areas that need improvement decreases, and the content of the first improvement plans presented changes. Therefore, by presenting only one first improvement plan, the user can feel that their oral condition is improving. Furthermore, even if there are multiple first improvement proposals, the first presentation control unit 1002 may select one first improvement proposal from the multiple first improvement proposals and present that selected first improvement proposal. In this case, the second presentation control unit 1003 generates and presents a second improvement proposal in accordance with the single first improvement proposal. One example of when the first presentation control unit 1002 selects and presents one first improvement proposal from multiple first improvement proposals is to present the first improvement proposal for the parameter with the worst score among those classified into a predetermined type. By having the first presentation control unit 1002 select and present a first improvement proposal, it is possible to provide the most suitable suggestion to a user who does not know which first improvement proposal to choose.

[0106] [Fourth Embodiment] A third embodiment of the present invention, the oral condition estimation system 1200, will now be described. The oral condition estimation system 1200 consists of a user terminal 710 and a server 720. The configuration of the oral condition estimation system 1200 will be described with reference to Figure 12.

[0107] In this embodiment, the user terminal 1210 is equipped with a self-check information acquisition unit 1211, a medical interview information acquisition unit 1212, and a presentation unit 1213 by installing an application program. The user terminal 1210 then transmits the acquired self-check information and medical interview information to the server 1220 via a network (not shown). The server uses the received self-check information to estimate the oral condition using the oral condition estimation unit, and uses the estimated oral condition and the medical interview information sent from the user terminal 1210 to classify the user's oral condition using the classification unit 1222. Using the classification results, the suggestion generation unit 1223 generates suggestion information regarding oral care, and transmits (replies to) the generated suggestion information to the user terminal 1210. The user terminal 1210 processes the received suggestion information as appropriate using the presentation unit 1213 and presents it to the user by displaying it on the screen.

[0108] The self-check information acquisition unit 1211 of the user terminal 1210 will be described in detail below. The self-check information acquisition unit includes a blood flow information acquisition unit, a microbiome information acquisition unit, and a saliva information acquisition unit (not shown).

[0109] The operation of the blood flow information acquisition unit is explained using Figure 13A. When the blood flow information acquisition unit is activated, the user terminal 1210 prepares to allow the user of the user terminal 1210, i.e., the user, to observe changes in blood flow in the gums (blood flow information acquisition preparation step S1301). In the blood flow information acquisition preparation step S1301, the gum image acquisition unit activates the selfie camera, which is located on the screen side of the built-in camera and is used to photograph the face of the operator facing the screen, and begins taking images. Then, to facilitate self-checking by the user, self-check assistance is performed by displaying self-check assistance information, which is an image taken by the selfie camera, on the screen. Following the blood flow information acquisition preparation step S511, the blood flow information measurement step S1303 is executed. Subsequently, in the blood flow information acquisition completion confirmation step S1305, it is confirmed that all timing information from three predetermined locations has been acquired. If the acquisition of the predetermined blood flow information is not complete (NO in the figure), the blood flow information measurement step S1303 is executed again. On the other hand, once it is confirmed that blood flow has been completed (YES in the diagram), the blood flow information acquisition unit sends the acquired blood flow information, i.e., the measured time, to the server (blood flow information transmission step S1307).

[0110] Step S1303, the blood flow information measurement step, will be explained in detail using Figure 13B. The blood flow information acquisition unit waits for 3 seconds with the first blood information acquisition instruction displayed on the screen: "Press the gum between the teeth (interdental papilla) in a position easily visible to the eye with your left index finger, and at the same time click the start button on the screen with your right hand" (blood flow stop step S1311). Then, it displays the second blood flow information acquisition instruction: "Remove your finger from your gums," and the timing unit starts measuring time (measurement start step S1313), i.e., the timer starts operating. Subsequently, it displays the third blood information acquisition instruction: "When your gums return to their original color, click the measurement button on the screen" (measurement end method presentation step S1315). Following the instructions, the user clicks the location on the screen where the measurement button is displayed, and the timing unit stops the timer, reads the time at that moment, and completes the measurement (time measurement step S1317). In other words, the blood flow information acquisition unit sequentially presents instructions for acquiring blood information to the user terminal 1210, more specifically, these instructions are displayed (presented) on the screen of the user terminal 1210. The unit accepts the input in response to these instructions, and the timing unit stops the timer based on the operation received by the blood flow information acquisition unit. The timing unit then reads the value, allowing the blood flow information acquisition unit to acquire blood flow information.

[0111] Once the transmission of blood information is complete, the blood information acquisition unit terminates its operation, and subsequently, the user terminal 710 proceeds to the microbiome information acquisition step S1203, at which point the microbiome information acquisition unit begins operation.

[0112] When the microbiome information acquisition unit is activated, it displays (presents) a first microbiome information acquisition instruction that instructs the user on actions and operations on the oral condition estimation device, for example, "Please clean between all your teeth using floss. Once you have finished cleaning, click the 'Next' button with tooth plaque still attached to the floss." When the user follows the instructions and finishes cleaning their teeth with floss and clicks the button, multiple samples of floss contamination levels are displayed on the screen as self-check support information, along with a second microbiome information acquisition instruction that says, "Please click the closest sample." When the user selects and clicks a sample, a third microbiome information acquisition instruction is then displayed (presented) on the screen that says, "Smell the floss. If you smell a strong odor, click 'Strong,' if you smell a weak odor, click 'Weak,' and if you smell no odor, click 'None.'" When a user clicks on the screen according to the instructions, the microbiome information acquisition unit receives the input from the user via that click and sends the acquired microbiome information—that is, the degree of floss contamination and the rank of the scent level as visually determined by the user—to the server.

[0113] Once the transmission of the microbiome information is complete, the microbiome information acquisition unit terminates its operation, and the user terminal 710 then proceeds to the saliva information acquisition step S1405, at which point the saliva information acquisition unit is activated.

[0114] When the saliva information acquisition unit is activated, it displays the first saliva information acquisition instruction, "Prepare five layers of tissue paper and one of the following: a 1-yen coin, a 5-yen coin, or a 10-yen coin, and click on the type of coin you have prepared," along with a schematic diagram of each coin on the screen. After the user prepares the tissue paper (hereinafter referred to as tissue) and coin and clicks on the screen, it then displays the second saliva information acquisition instruction, "Collect saliva." After 30 seconds, the saliva information acquisition unit replaces the second saliva information acquisition instruction with a third saliva information acquisition instruction, "Spit the saliva you have collected onto the tissue, place the coin next to it, and then click on the screen," instructing the user on what to do and how to operate it. When the screen is clicked, multiple images of saliva stains of different sizes are displayed next to the coin as self-check aid information, and the fourth saliva information acquisition instruction is displayed, "Select the image that you think is the closest and click on it." When the user clicks according to the instructions, the saliva information acquisition unit accepts the input and sends the acquired saliva information, specifically the size of the saliva stain based on the size of a coin as determined by the user's visual inspection, to the server.

[0115] Upon receiving blood and saliva information, the server 1220 uses the oral condition estimation unit 1221 to estimate the oral condition.

[0116] When the saliva information acquisition unit transmits the size of the saliva stain, based on the size of a coin visually determined by the user, to the server, the self-check information acquisition unit 1211 terminates its operation, and the user terminal 1210 then moves to the medical interview information acquisition step S1407, in which case the medical interview information acquisition unit 1212 is activated. The user terminal 1210 transmits the medical interview information acquired through the user's operation to the server 1220. The acquisition of medical interview information by the medical interview information acquisition unit 1212 is the same as in the second embodiment, so its explanation is omitted. Unlike the medical interview information acquisition unit 601 in the second embodiment, the medical interview information acquisition unit 1212 in this embodiment not only acquires medical interview information but also transmits it to the server 1220.

[0117] Once the server 1220 has completed the estimation of the oral condition by the oral condition estimation unit 1221 and the reception of the medical questionnaire information sent from the user terminal 710, the classification unit 722 classifies the oral condition. After the classification of the oral condition by the classification unit 1222 is completed, the suggestion generation unit 1223 is activated and generates suggestions according to the classification. The operation of the suggestion generation unit 1223 for generating suggestion information is the same as that of the suggestion generation unit 602 in the second embodiment, so it is omitted here. The suggestion information generated by the suggestion generation unit is transmitted to the user terminal 1210 via the network by a transmission unit (not shown).

[0118] In the proposal reception step S1409, once the user terminal 1210 has finished receiving the proposal information from the server 1220, it moves to the presentation step S1411. The presentation unit processes the information to make it easier for the user to understand and displays it on a screen (not shown) of the user terminal 1210.

[0119] In other words, when the application program is launched, the user terminal executes the blood flow information acquisition step S1401, as shown in Figure 14, followed sequentially by the microbiome information acquisition step S1403, the saliva information acquisition step S1405, the medical history information acquisition step S1407, the suggestion reception step S1409, and the presentation step S1411.

[0120] In this embodiment, the presentation unit presents suggestions to the user, but the presentation unit may also present the results of classification by the classification unit. In that case, suggestions may or may not be presented to the user. That is, the suggestion generation unit 1223 may be omitted. Alternatively, the presentation unit 1213 may be configured to present only the estimation results by the oral condition estimation unit 1221 to the user, without the suggestion generation unit 1223 or the classification unit 1222. In this case, it is preferable that the oral condition estimation unit 1221 is provided on the user terminal 1210, and that the oral condition estimation device of the present invention is configured solely on the user terminal 1210.

[0121] As described above, in this embodiment, by including self-check sample information (self-check support information), such as images taken by a selfie camera, images of saliva stains of different sizes lined up next to a coin, and samples of the degree of floss contamination, in the user's actions and the instructions for operation to the oral condition estimation device, the burden on the user's self-check work can be reduced, and the accuracy of the self-check can be improved.

[0122] Although the present invention has been described above with reference to embodiments, the present invention is not limited to the embodiments described above and can be modified as appropriate. The configuration of the present invention can be modified in various ways that can be understood by those skilled in the art within the scope of the present invention. For example, instructions for the user's actions to acquire self-check information or instructions for operating the oral condition estimation device may not be displayed on the screen, but may be presented from a speaker by automated voice or the like. User input may also be acquired not only by clicking on the screen, but also by using a keyboard or other input device, or by receiving the user's speech through a microphone. Furthermore, the order in which each piece of self-check information is acquired does not have to be the order disclosed above. Specifically, the blood information acquisition step, the microbiome information acquisition step, and the saliva information acquisition step may be performed in any order.

[0123] Furthermore, any system or device that combines the different features included in each embodiment in any way is also included within the scope of the present invention. For example, the invention may be configured to present only estimation results or classification results without presenting any proposals.

[0124] Furthermore, the present invention may be applied to a system composed of multiple devices or to a single device. Moreover, the present invention is also applicable when an information processing program that realizes the functions of the embodiment is supplied to a system or device and executed by a built-in processor. Therefore, the technical scope of the present invention includes programs installed on a computer, media containing such programs, WWW (World Wide Web) servers that allow the program to be downloaded, and processors that execute such programs, all necessary for realizing the functions of the present invention on a computer. In particular, at a minimum, a non-transitory computer-readable medium containing a program that causes a computer to execute the processing steps included in the above-described embodiment is included. A readable medium is included within the technical scope of this invention.

Claims

1. A self-check information acquisition unit that acquires self-check information, which is information obtained when a user self-checks the inside of their own mouth, Based on the self-check information, the oral condition estimation unit estimates the user's oral condition, An oral condition estimation device equipped with the following features.

2. The oral condition estimation device according to claim 1, further comprising a classification unit that classifies the user's oral condition into predetermined types based on the oral condition of the user estimated by the oral condition estimation unit.

3. The oral condition estimation device according to claim 1, wherein the self-check information acquisition unit presents the user with instructions for actions to take or operations to perform on the oral condition estimation device in order to acquire the self-check information, and accepts operations from the user in accordance with the instructions, thereby acquiring the self-check information.

4. The oral condition estimation device according to claim 3, wherein a sample for self-checking is included in the user's actions or instructions for operating the oral condition estimation device to acquire the self-checking information.

5. The self-check information acquisition unit uses the following as the self-check information: When the user presses on their gums with their finger and then releases it, the blood flow status information is the time it takes for the gums to return to their original color, When the user performs interdental cleaning using dental floss, the bacterial flora status information includes at least one of the degree of soiling, odor, and blood contamination of the dental floss, When the user spits saliva that has been held in the mouth for a predetermined time onto a predetermined piece of paper, the saliva state information is based on the area over which the spit-out saliva spreads on the predetermined piece of paper, Obtain, The oral condition estimation unit is, A blood flow state estimation unit that estimates the blood flow state of the user's gums from the blood flow state information, A microbiome state estimation unit that estimates the microbiome state in the user's oral cavity from the aforementioned microbiome state information, A saliva state estimation unit that estimates the user's saliva state from the aforementioned saliva state information, It further possesses, The oral cavity state estimation device according to claim 2, wherein the classification unit classifies the oral cavity state of the user into the predetermined type based on at least one of the estimated blood flow state, microbiota state and saliva state of the user.

6. A medical information acquisition unit acquires medical information regarding the user's responses to a medical questionnaire about their oral condition. The oral condition estimation device according to claim 1, wherein the oral condition estimation unit estimates the user's oral condition based on the acquired medical interview information and the self-check information.

7. A proposal generation unit that generates a proposal for at least one of an oral care product and an oral care method to promote improvement of the user's oral condition, based on the estimated oral condition. A presentation unit that presents the estimated oral condition and the generated proposal to the user, The oral condition estimation device according to claim 1 or 2, further comprising the above.

8. The oral condition estimation device according to claim 1, wherein the self-check information acquisition unit further acquires an image or video of the user's oral cavity.

9. The oral condition estimation device according to claim 2, wherein the predetermined type is derived by analyzing parameters indicating the oral condition of multiple people.

10. The oral condition estimation device according to claim 9, wherein the predetermined type is derived by analyzing the parameters while further taking into account information on the lifestyle habits of the multiple persons.

11. A first presentation control unit presents the user with the classified predetermined type and allows the user to select and present a first improvement plan for the user's oral cavity condition corresponding to the predetermined type. A second presentation control unit generates a second improvement proposal for the user, based on the classified predetermined type and the first improvement proposal selected by the user, which is to promote the improvement of the user's oral condition, and presents the generated second improvement proposal to the user. The oral condition estimation device according to claim 9 or 10, further comprising the above.

12. A first presentation control unit that presents a first improvement plan for the user's oral cavity condition according to the classified predetermined type, A second presentation control unit generates a second improvement proposal for at least one of an oral care product and a lifestyle improvement proposal to promote improvement of the user's oral condition, based on the classified predetermined type and the first improvement proposal, and presents the generated second improvement proposal to the user. The oral condition estimation device according to claim 9 or 10, further comprising the above.

13. A method for classifying oral conditions, which is performed by an information processing device, The process involves a self-check information acquisition step, which involves obtaining self-check information obtained by the user performing a self-check of their own oral cavity, and Based on the self-check information, an oral condition estimation step is performed to estimate the oral condition of the user, A method for estimating oral condition, including the following.

14. The process involves a self-check information acquisition step, which involves obtaining self-check information obtained by the user performing a self-check of their own oral cavity, and Based on the self-check information, an oral condition estimation step is performed to estimate the oral condition of the user, A program that uses a computer to estimate the oral condition.

15. It consists of user terminals and servers connected via a network. It comprises a self-check information acquisition unit, an oral condition estimation unit, and a presentation unit. An oral condition estimation system comprising an oral condition estimation unit that performs estimation using at least the self-check information acquired by the self-check information acquisition unit, and a presentation unit that presents information based on the estimation to the user.

16. A user terminal for an oral condition estimation system that estimates oral condition, A user terminal equipped with a self-check information acquisition unit.

17. A user terminal according to claim 16, The self-check information acquisition unit is a user terminal that presents the user with instructions for actions to take or operations on an oral condition estimation device to acquire self-check information, and acquires the self-check information by accepting operations from the user in accordance with the instructions.

18. A user terminal according to claim 17, The user's actions or instructions for operating the oral condition estimation device to obtain the aforementioned self-check information are provided by a user terminal that includes sample information for self-checking.

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