Evaluation device, evaluation method, evaluation model generation method, and evaluation program

Abstract

Provided are an evaluation device and the like capable of evaluating a brushing technique for removing bacterial plaque. An evaluation device (1) is provided with: an index value calculation unit (102) that calculates an index value indicating a brushing range on the basis of acceleration data indicating the acceleration of a toothbrush when a subject brushes teeth; and a skill evaluation unit (104) that calculates an evaluation value of the brushing skill of the subject on the basis of the index value calculated by the index value calculation unit (102) by using a brushing skill evaluation model (111) generated on the basis of the correlation between the index value and the plaque removal rate.

Description

Technical Field

[0001] The present invention relates to an evaluation device for evaluating tooth brushing, etc. Background Art

[0002] Technologies for evaluating a subject's toothbrushing and providing feedback on its effectiveness are known. For example, Patent Document 1 below describes a technique for brushing teeth using a toothbrush equipped with a built-in acceleration sensor. The technique describes analyzing the output signal of the acceleration sensor to determine the number of brushing cycles for a specific tooth surface area. The number of brushing cycles is then compared with a pre-set reference value for that area, thereby evaluating the brushing performance of that area.

[0003] (Prior art literature)

[0004] (Patent Document)

[0005] Patent Document 1: Japanese Patent Application No. 2013-536018. Summary of the Invention

[0006] (Problems to be solved by the invention)

[0007] It's understandable that the technology in Patent Document 1 is based on the assumption that brushing is successful if the number of brushing cycles exceeds a reference value. However, in reality, even when brushing the toothbrush the same number of times, differences in brushing technique can lead to differences in brushing effectiveness. For example, when comparing a toothbrush with a large brushing motion to a small one, the former tends to leave plaque between teeth and between teeth and gums. Furthermore, plaque in these areas can potentially contribute to dental caries or periodontal disease.

[0008] Therefore, the above-mentioned prior art has the problem of being unable to evaluate the brushing skill for removing bacterial plaque. One aspect of the present invention is to provide an evaluation device, etc., which can evaluate the brushing skill for removing bacterial plaque.

[0009] (Technical means used to solve the problem)

[0010] To solve the above-mentioned problem, an evaluation device according to one aspect of the present invention comprises: an index value calculation unit, which calculates an index value representing the brushing amplitude based on the toothbrush acceleration data of the subject when brushing his teeth; and a skill evaluation unit, which uses an evaluation model of brushing skill generated based on the correlation between the index value and the plaque removal rate, and calculates an evaluation value of the brushing skill of the subject based on the index value calculated by the index value calculation unit.

[0011] In addition, to solve the above-mentioned problem, an evaluation method according to one aspect of the present invention is an evaluation method executed by one or more information processing devices, and the evaluation method includes: an index value calculation step, in which an index value representing the brushing amplitude is calculated based on the toothbrush acceleration data when the subject is brushing his teeth; a skill evaluation step, in which an evaluation model of brushing skill is generated based on the correlation between the index value and the plaque removal rate, and an evaluation value of the brushing skill of the subject is calculated based on the index value calculated in the index value calculation step.

[0012] In addition, to solve the above-mentioned problem, a method for generating an evaluation model in one aspect of the present invention is a method for generating an evaluation model executed by one or more information processing devices, and the generation method includes: a formulation step of formulating the correlation between the index value representing the brushing amplitude calculated based on the toothbrush acceleration data during brushing and the plaque removal rate of the brushing; and a model generation step of generating an evaluation model for calculating the brushing skill evaluation value based on the index value based on the function obtained by the formulation.

[0013] The evaluation devices involved in various aspects of the present invention may also be implemented using a computer. In this case, an evaluation device control program that causes a computer to operate the various components (software elements) of the evaluation device, thereby implementing the evaluation device using a computer, and a computer-readable recording medium having the control program recorded thereon also fall within the scope of the present invention.

[0014] (Effects of the Invention)

[0015] According to one aspect of the present invention, an evaluation device or the like capable of evaluating brushing skills for removing bacterial plaque can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a block diagram showing an example of the configuration of main parts of an evaluation device according to one embodiment of the present invention.

[0017] Figure 2 FIG. 1 is a schematic diagram of a configuration example of an evaluation system including the evaluation device.

[0018] Figure 3 This is a block diagram showing an example of the configuration of the main parts of the model generation device included in the evaluation system.

[0019] Figure 4 4001 represents the relationship between the index value and the plaque removal rate, and 4002 represents an example of an evaluation model.

[0020] Figure 5 5001 shows the relationship between the index value and the plaque removal rate when the toothbrush type is different from 4001, and 5002 shows another example of the evaluation model.

[0021] Figure 6 This is a flowchart showing an example of the process of generating an evaluation model.

[0022] Figure 7 This is a schematic diagram of an example of a brush pressure evaluation model.

[0023] Figure 8 This is a schematic diagram of an example of an angle evaluation model.

[0024] Figure 9 This is another example diagram of the angle evaluation model.

[0025] Figure 10 This is a flowchart showing an example of the process of calculating the brushing skill evaluation value.

[0026] <Description of Reference Numerals>

[0027] 1 Evaluation device

[0028] 102 Index Value Calculation Department

[0029] 103 Type Identification Unit

[0030] 104 Skills Assessment Department

[0031] 105 Time Assessment Department

[0032] 108 Comprehensive Assessment Department

[0033] 111 Evaluation Model

[0034] 2 toothbrushes DETAILED DESCRIPTION

[0035] [Composition of the evaluation system]

[0036] based on Figure 2 , the structure of the evaluation system 100 according to one embodiment of the present invention is described. Figure 2 1 is a schematic diagram of a configuration example of an evaluation system 100 including an evaluation device 1. The evaluation system 100 has a function of evaluating the brushing technique (hereinafter referred to as brushing technique) of a subject when brushing with a toothbrush 2. Figure 2 As shown, the evaluation system 100 includes an evaluation device 1, a toothbrush 2, and a model generation device 4. The toothbrush 2 includes an acceleration sensor (not shown) and transmits sensor data during brushing to the evaluation device 1.

[0037] Here, the toothbrush 2 can be either an electric toothbrush, where the bristles of the brush are moved by electricity, or a manual toothbrush where the user manually brushes. Furthermore, the portion containing the built-in sensor and the like can be detachably connected to the brush portion. In this case, a worn brush portion can be replaced while maintaining the sensing and communication functions of the toothbrush 2.

[0038] Previously, it was impossible to evaluate brushing techniques that effectively remove plaque that can lead to caries or periodontal disease. To address this, the inventors of this application conducted experiments to investigate the relationship between brushing amplitude and plaque removal rate. They found that brushing amplitude within a specific range improves plaque removal rate, indicating a correlation between brushing amplitude and plaque removal rate.

[0039] The evaluation system 100 uses the sensor data during brushing to evaluate the brushing technique using the evaluation model 111 generated based on the correlation. Thus, the evaluation system 100 can evaluate the brushing technique for removing plaque.

[0040] The evaluation result of the brushing skill may be displayed on, for example, the display unit 14 included in the evaluation device 1 . Figure 2 In the example of FIG, the display unit 14 displays the brushing skill evaluation value V1, the brushing time evaluation value V2, and the comprehensive evaluation value V3. Details of the brushing time evaluation value and the comprehensive evaluation value will be described later.

[0041] [Composition of the model generation device]

[0042] based on Figure 3 Next, the model generation device 4 will be described. The model generation device 4 generates an evaluation model 111. This evaluation model 111 is a brushing skill evaluation model generated based on the correlation between the index value and the plaque removal rate. As described above, the evaluation device 1 uses the evaluation model 111 to calculate the evaluation value of the brushing skill. The model generation device 4 includes a control unit 40, a storage unit 41, a communication unit 42, and an input unit 43.

[0043] The control unit 40 centrally controls the various components of the model generation device 4. In one example, the control unit 40 may be a CPU (Central Processing Unit). The control unit 40 reads the control program stored in the storage unit 41 as software and expands it into a memory such as RAM (Random Access Memory) to execute various functions. The structure of the control unit 40 will be described in detail later.

[0044] The storage unit 41 stores various data used by the model generation device 4. For example, the storage unit 41 may store the estimation model 111 generated by the model generation device 4. Alternatively, the estimation model 111 may be generated for each type of toothbrush. In this case, the storage unit 41 may store a different estimation model 111 for each type of toothbrush.

[0045] The communication unit 42 is used to enable the model generation device 4 to communicate with other devices. For example, the model generation device 4 can also transmit the evaluation model 111 to the evaluation device 1 via the communication unit 42. The evaluation model 111 does not necessarily need to be provided to the evaluation device 1 via communication. For example, the evaluation model 111 can be stored in the evaluation device 1 before the product is shipped.

[0046] The input unit 43 receives input of various data to the model generation device 4. For example, various data required for generating the estimation model 111 may be input via the input unit 43. Here, the data may also be acquired via the communication unit 42.

[0047] [Composition of the control unit]

[0048] The control unit 40 includes an information acquisition unit 401 , an index value calculation unit 402 , a removal rate determination unit 403 , a formulation unit 404 , and a model generation unit 405 .

[0049] The information acquisition unit 401 acquires various data required for generating the evaluation model 111. The various data include sensor data measured when a plurality of subjects perform brushing, and the plaque removal rate obtained by the brushing.

[0050] Index calculation unit 402 calculates an index value representing the brushing amplitude for each subject. Excessive brushing amplitude tends to leave plaque between teeth and between teeth and gums. Therefore, this index value is suitable for evaluating brushing technique for plaque removal. Brushing amplitude can also be described as the degree of small brushing movements.

[0051] The index value can be any value representing the brushing amplitude or degree of small movements, and its calculation method is not particularly limited. For example, if a three-axis acceleration sensor is installed on the toothbrush used by the test subject to measure acceleration data during the brushing process, the information acquisition unit 401 can also obtain this acceleration data, and the index value calculation unit 402 can also use this acceleration data to calculate the index value.

[0052] When calculating the index value using acceleration data, the index value calculation unit 402 may also calculate the index value using the length of the combined acceleration vector obtained by combining the three-axis acceleration data. This combined vector length is expressed as follows: x_filtered, y_filtered, and z_filtered in Formula 1 are obtained by excluding the gravity acceleration component from the acceleration components in the orthogonal X, Y, and Z axis directions.

[0053] [Mathematical formula 1]

[0054]

[0055] In this case, the indicator value calculation unit 402 can, for example, perform the following processing: based on the acceleration data in the time series from the time when the subject starts brushing to the time when brushing ends, determine the period during which the toothbrush completes one reciprocating motion, or the period during which brushing of a specific part is completed, and calculate the synthetic vector length based on the average value of the acceleration of each axis component during the period, and use the calculated synthetic vector length as the indicator value.

[0056] The removal rate determination unit 403 determines the plaque removal rate corresponding to the index value calculated by the index value calculation unit 402. If the information acquisition unit 401 acquires information indicating the plaque removal rate of each subject, the removal rate determination unit 403 can use this information to determine the plaque removal rate corresponding to the index value calculated by the index value calculation unit 402.

[0057] Alternatively, the information acquisition unit 401 may acquire the test results of the plaque adhesion information after brushing by each subject. In this case, the removal rate determination unit 403 may calculate the plaque removal rate based on the test results.

[0058] Regarding the plaque removal rate to be determined by the removal rate determination unit 403, it is not limited to which calculation method is used. For example, the plaque removal rate can be calculated using the PCR (O'Leary's Plaque Control Record) 6-partition method. In the PCR six-partition method, each single side of any tooth to be tested is divided into three areas: proximal, central, and distal. For example, if a person has 28 teeth in the upper and lower jaws, then (the number of tested tooth surfaces in the upper and lower jaws) = 28 × 3 × 2 = 168. Then, the PCR value representing the proportion of plaque attachment areas among these areas is calculated, and the difference in PCR values ​​before and after brushing relative to the PCR value before brushing is used as the ratio of the plaque removal rate.

[0059] That is, PCR (%) = (number of tooth surfaces with plaque attached / number of tooth surfaces tested) × 100. For example, if 50 of 100 areas with plaque before brushing still have plaque after brushing, then PCR = (50 / 100) × 100 = 50 (%).

[0060] Plaque removal rate (%) = 100 × {(PCR before brushing - PCR after brushing) / (PCR before brushing)}. For example, if the PCR before brushing is 50% and the PCR after brushing is 20%, the plaque removal rate is 100 × (50 - 20) / 50 = 60%.

[0061] The calculation of plaque removal rate is not limited to the aforementioned six-zone PCR method; any index may be used. For example, the four-zone PCR method, the PCR variation method, the OHI (Oral Hygiene Index), the QHI (Modified Quingley-Hein Plaque Index), etc. may also be used to calculate the plaque removal rate.

[0062] For example, the removal rate determination unit 403 can also determine the average value of the plaque removal rate of the brushing action on the entire upper and lower jaws measured with acceleration data (i.e., the source data of the index value to be calculated by the index value calculation unit 402) as the plaque removal rate corresponding to the index value.

[0063] Formulating unit 404 formulates the correlation between the corresponding index value of the subject's brushing and the plaque removal rate of the brushing. As described above, the index value is calculated by index value calculation unit 402, and the plaque removal rate is determined by removal rate determination unit 403. Therefore, formulating unit 404 only needs to formulate the relationship between the two.

[0064] Figure 4 4001 shows the relationship between the index value and the plaque removal rate. Figure 4 The points shown in 4001 in FIG. 4 represent the index value and plaque removal rate calculated for each subject. The inventors of the present application have found that the relationship between the index value and the plaque removal rate is shown in the curve Figure 4 As shown in 4001 in FIG, it protrudes toward the positive direction of the y-axis.

[0065] The formulating unit 404 formulates such a relationship. For example, the formulating unit 404 can fit the relationship by a quadratic function. Figure 4 The points shown in 4001 are fitted, and the formula can be expressed as y = -0.0027x 2 +0.9307x-10.517 to proceed.

[0066] The model generation unit 405 generates, based on the formulated function, an evaluation model 111 for calculating a toothbrushing skill evaluation value from an index value calculated when toothbrushing serving as an evaluation target is performed.

[0067] Figure 4 4002 shows the Figure 4The evaluation model 111A generated based on the relationship between the index value and the plaque removal rate shown in 4001. The evaluation model 111A is an example of the evaluation model 111. In the evaluation model 111A, when looking at the range where the index value is 150 to 200, the evaluation value of the brushing technique is the highest score of 100 points, and the further away from this range, the lower this evaluation value. For example, at the point where the index value is 70 and at the point where the index value is 270, this evaluation value is 60 points.

[0068] To generate such an evaluation model 111A, the model generation unit 405 can, for example, also use the function generated by the formula unit 404 to determine the index value range corresponding to the plaque removal rate above the first threshold TH1, and generate a formula component where the evaluation values corresponding to the index values within this range are all the maximum value (for example, 100 points). Subsequently, the model generation unit 405 can also determine the index value range corresponding to the plaque removal rate less than the second threshold TH2 (TH2 < TH1), and generate a formula component where the evaluation values corresponding to the index values within this range are all the minimum value (for example, 60 points). Also, the model generation unit 405 can set a formula component where the evaluation values for other ranges decrease monotonically from the maximum value to the minimum value. Thus, the model generation unit 405 can generate a formula shown as the curve in Figure 4 4002 as the evaluation model 111.

[0069] Here, the method of formulaization is not limited to the above example. For example, the model generation unit 405 can also generate an evaluation model 111 that converts the y - coordinate value (plaque removal rate) of the function obtained through the formulaization process of the formula unit 404 into an evaluation value. Also, for example, the model generation unit 405 can generate the following evaluation model 111: multiply the value calculated by the function obtained through the formulaization process of the formula unit 404 by n times (n > 0) to convert it into an evaluation value, so that the evaluation value when the y - coordinate value of the function obtained through the formulaization process of the formula unit 404 is the maximum value is the maximum value. In this example, if the function obtained through the formulaization process of the formula unit 404 is y = -0.0027x 2 + 0.9307x - 10.517, then the result of the evaluation model is (evaluation value) = n(-0.0027x 2 + 0.9307x - 10.517).

[0070] Here, the relationship between the index value and the plaque removal rate may vary depending on the type of toothbrush used, etc. Figure 5 5001 in shows the relationship between the index value and the plaque removal rate obtained using a toothbrush different from that in Figure 4 4001. Figure 55002 in the figure shows an evaluation model 111B based on the relationship between the index value and the evaluation value shown in 5001. Here, the differences in toothbrush types include at least one of differences in bristle pattern, filament material, filament diameter, bristle length, bristle tip shape, brush head base thickness, brush head shape, and number of bristles.

[0071] By comparison Figure 4 4001 and Figure 5 As can be seen from the 5001 in the figure, the relationship between the brushing amplitude and the plaque removal rate may vary depending on the type of toothbrush used. For example, Figure 5 The relationship shown in 5001 is formulated as y=-0.0011x by the formulating unit 404. 2 +0.5722x-7.972.

[0072] Here, in Figure 5 In the evaluation model 111B shown in Figure 5002, the reduction rate of the evaluation value corresponding to the range of index values ​​above 240 is set to be large, and the evaluation value corresponding to the range of index values ​​above 300 is set to the minimum value (60 points). This setting is made in consideration of the fact that brushing can damage the gums. In other words, if the relationship between the index value representing the brushing amplitude and the plaque removal rate is as follows Figure 5 If, as shown in Figure 5001, a high plaque removal rate is achieved even with a wide range of brushing, then directly incorporating this relationship into the evaluation model would likely result in a high evaluation of intense brushing that could cause gum damage. Therefore, in evaluation model 111B, as described above, the evaluation value is lowered for ranges with high index values ​​to prevent encouraging intense brushing that could cause gum damage.

[0073] In this manner, the model generation unit 405 may generate an evaluation model 111B in which the evaluation value decreases as the index value increases within a range above a predetermined value. Furthermore, the model generation unit 405 may set the rate of decrease to be greater than the rate of decrease in the evaluation value as the index value decreases within a range below the predetermined value. This allows the generation of an evaluation model 111B that outputs a high evaluation value for brushing that does not injure the gums and a low evaluation value for intense brushing that may injure the gums, thereby encouraging brushing within the range where the gums are not injurious.

[0074] The model generating device 4 can also generate in advance Figure 4 and Figure 5Evaluation models 111 corresponding to the type of toothbrush 2, such as evaluation models 111A and 111B shown, are generated and provided to the evaluation device 1. This allows the evaluation device 1 to calculate an appropriate evaluation value by applying the evaluation model 111 corresponding to the type of toothbrush 2 used by the evaluation subject. Alternatively, if the type of toothbrush 2 used by the evaluation subject changes, the evaluation device 1 can obtain an evaluation model 111 corresponding to the new type of toothbrush 2 from the model generation device 4. This approach also achieves the same effects as described above.

[0075] [Processing Flow (Evaluation Model Generation Method)]

[0076] Figure 6 111 is a flowchart showing an example of the process of generating the evaluation model 111. Figure 6 As shown, in step S1, the acceleration data measured when each subject performs brushing is acquired by the information acquisition unit 401. Here, the acceleration data may also include acceleration data of each brushing session performed by a subject.

[0077] In step S2, as preprocessing, the index value calculation unit 402 removes the gravity component from the acceleration data acquired in step S1. Then, in step S3, the index value calculation unit 402 calculates an index value representing the brushing amplitude using the acceleration data preprocessed in step S2. Here, the index value is calculated for each of the multiple subjects.

[0078] In step S4, the removal rate determination unit 403 determines the plaque removal rate corresponding to each index value calculated in step S3. As described above, the plaque removal rate can be input by the user, or the removal rate determination unit 403 can calculate the plaque removal rate by inputting raw data for calculating the plaque removal rate.

[0079] In step S5 (formulation step), the formulating unit 404 formulates the correlation between the index value calculated in step S3 and the plaque removal rate determined in step S4. As described above, the formulating unit 404 can formulate the correlation by, for example, fitting based on a quadratic function.

[0080] In step S6 (model generation step), the model generation unit 405 generates an evaluation model 111 based on the function formulated in step S5, which is used to calculate the brushing skill evaluation value based on the index value calculated when the toothbrushing subject is being evaluated. The model generation unit 405 then stores the generated evaluation model 111 in the storage unit 41.

[0081] Here, each function of the model generation device 4 can also be realized by a system composed of multiple information processing devices. Figure 6 The execution subjects of each step shown are not limited to the above examples. Figure 6 Each of the steps shown may be executed by one information processing device, or may be executed by having a plurality of information processing devices share the processing of each step.

[0082] As described above, the method for generating the evaluation model 111 of this embodiment is a method for generating the evaluation model 111 executed by one or more information processing devices, and includes: (1) a formulating step (step S5) of formulating the correlation between the index value representing the brushing amplitude calculated based on the toothbrush acceleration data during brushing and the plaque removal rate of the brushing; and (2) a model generating step (step S6) of generating the evaluation model 111 based on the formulated function, wherein the evaluation model 111 is used to calculate the evaluation value of the brushing skill based on the index value calculated when the toothbrush is brushing as the evaluation object. In this way, the following evaluation model 111 can be generated: it is possible to calculate the evaluation value of the brushing skill of the subject based on the index value representing the brushing amplitude of the subject. And by using the evaluation model 111 generated in this way, the brushing skill of the subject for removing plaque can be evaluated.

[0083] In addition, in the formulation step (step S5), the correlation between the plaque removal rate calculated for multiple areas divided on the surface of each tooth and the index value is formulated, so that an evaluation value reflecting whether the plaque in every corner of each tooth has been successfully removed can be calculated.

[0084] [Composition of the evaluation device]

[0085] based on Figure 1 , the structure of the evaluation device 1 is described. Figure 1 This is a block diagram of an example of the main components of the evaluation device 1. The evaluation device 1 is a device for calculating the evaluation value of the brushing skill. Figure 1 As shown, the evaluation device 1 includes a control unit 10 , a storage unit 11 , a communication unit 12 , an input unit 13 , and a display unit 14 .

[0086] The control unit 10 centrally controls the various components of the evaluation device 1. In one example, the control unit 10 may be a CPU. The control unit 10 reads a control program stored in the storage unit 11 as software and expands it into a memory device such as RAM to execute various functions. The structure of the control unit 10 will be described in detail later.

[0087] The storage unit 11 stores various data used by the evaluation device 1. The storage unit 11 may also pre-store an evaluation model 111, a brushing pressure evaluation model 112, and an angle evaluation model 113 corresponding to each type of toothbrush 2. The brushing pressure evaluation model 112 and the angle evaluation model 113 will be described in detail later.

[0088] The communication unit 12 is used to communicate with other devices (e.g., the toothbrush 2 and the model generation device 4). The input unit 13 receives various data inputs for the evaluation device 1. For example, the input unit 13 receives input from the subject regarding the type of toothbrush 2. Alternatively, the toothbrush 2 can detect the type of its own brush head and notify the evaluation device 1 accordingly.

[0089] The display unit 14 displays information generated based on display information acquired from the display control unit 109 described later. Here, the display unit 14 may not be provided in the evaluation device 1, but may be provided outside the evaluation device 1 and connected to the evaluation device 1.

[0090] [Composition of the control unit]

[0091] The control unit 10 includes an information acquisition unit 101 , an index value calculation unit 102 , a type identification unit 103 , a skill evaluation unit 104 , a time evaluation unit 105 , a swipe pressure evaluation unit 106 , an angle evaluation unit 107 , a comprehensive evaluation unit 108 , and a display control unit 109 .

[0092] The information acquisition unit 101 acquires various data required for calculating the brushing skill evaluation value, including the brushing acceleration data and brushing pressure data of the subject.

[0093] The index value calculation unit 102 calculates an index value representing the brushing amplitude based on the acceleration data of the toothbrush 2 when the subject is brushing their teeth. The index value calculation unit 102 can calculate the index value using the same method as the index value calculation unit 402 of the model generation device 4.

[0094] The type identification unit 103 identifies the type of toothbrush 2 used by the subject. For example, the type of toothbrush 2 may be input by the subject, etc. In this case, the type identification unit 103 identifies the type of toothbrush 2 based on the input received by the input unit 13 or the communication unit 12. In this embodiment, the control unit 10 does not necessarily need to include the type identification unit 103, but it is preferred that the control unit 10 include the type identification unit 103.

[0095] The skill evaluation unit 104 uses the evaluation model 111 to calculate an evaluation value of the subject's brushing skill based on the index value calculated by the index value calculation unit 102. If an evaluation model 111 corresponding to the type of toothbrush 2 is available, the skill evaluation unit 104 calculates the evaluation value using the evaluation model 111 corresponding to the identification result of the type identification unit 103, among a plurality of evaluation models 111 pre-generated for each type of toothbrush.

[0096] Thus, the evaluation value can be calculated using the evaluation model 111 corresponding to the type of toothbrush used by the subject, and therefore an appropriate evaluation value according to the type of toothbrush 2 used can be calculated.

[0097] For example, it is conceivable that the subject used Figure 4 The toothbrush 2 corresponding to the evaluation model 111A shown in FIG4002 is used for brushing teeth. In this case, if the index value calculated by the index value calculation unit 102 is 150, the evaluation value calculated by the skill evaluation unit 104 based on the evaluation model 111A is 100 points.

[0098] The skill evaluation unit 104 can calculate the evaluation value in real time during the brushing process or after the brushing process. If the evaluation value is calculated in real time during the brushing process, the index value calculation unit 102 calculates the index value in real time based on the acceleration data measured in the time series during the brushing process. The skill evaluation unit 104 then inputs the index value calculated in real time by the index value calculation unit 102 into the evaluation model 111 to calculate the evaluation value of the brushing skill. On the other hand, if the evaluation value is calculated after the brushing process, the skill evaluation unit 104 calculates the evaluation value using a representative value (e.g., average value, maximum value, etc.) among the index values ​​in the time series calculated by the index value calculation unit 102 based on the acceleration data measured during the brushing process.

[0099] The skill evaluation unit 104 can calculate the evaluation value for the entire upper and lower jaws or for each region within the oral cavity. When calculating the evaluation value for each region, the skill evaluation unit 104 can use a representative value from the time-series index values ​​calculated by the index value calculation unit 102 based on the acceleration data measured during the brushing of the evaluation region.

[0100] Furthermore, the skill evaluation unit 104 may correct the evaluation value based on, for example, the location on the tooth surface that is contacted by the brush portion of the toothbrush 2 .

[0101] The time evaluation unit 105 calculates an evaluation value for the subject's brushing duration. For example, the time evaluation unit 105 measures the brushing duration for both upper and lower jaws and evaluates the brushing duration based on this brushing duration and a preset standard brushing duration for both upper and lower jaws. For example, if the standard brushing duration is 2 minutes and the brushing duration is 1 minute, the time evaluation unit 105 can calculate the evaluation value as: evaluation value = 1 minute / 2 minutes × 100 = 50. By including the time evaluation unit 105, the evaluation device 1 can perform a comprehensive brushing assessment that also takes into account brushing duration.

[0102] In addition, the time evaluation unit 105 can not only calculate the evaluation value for the brushing time of the upper and lower jaws as a whole, but also calculate the evaluation value for the brushing time of each area divided in the oral cavity. In addition, in addition to setting an area containing multiple teeth, the time evaluation unit 105 can also evaluate the brushing time of each tooth as a separate area. In this case, the standard time length can be pre-set for each area. In addition, when evaluating the brushing time for each area, the skill evaluation unit 104 can also calculate the evaluation value for each area. Here, in this embodiment, the control unit 10 does not necessarily have the time evaluation unit 105, but it is preferred that the control unit 10 has the time evaluation unit 105.

[0103] The brushing pressure estimator 106 calculates an evaluation value for the brushing pressure applied to the subject's teeth while brushing. For example, the brushing pressure estimator 106 may use the brushing pressure estimation model 112 to calculate this evaluation value. The brushing pressure estimation model 112 may also be a function that returns a higher evaluation value for brushing pressure within an appropriate range and a lower evaluation value for brushing pressures that deviate further from the appropriate range.

[0104] Figure 7 FIG. 1 is a schematic diagram of an example of the brush pressure evaluation model 112 . Figure 7 The brush pressure evaluation model 112 shown represents an upwardly convex curve. When the optimal brush pressure is input to this model 112, it outputs the maximum evaluation value. Furthermore, as the input brush pressure deviates from the optimal value, the evaluation value output by the model 112 decreases. The model 112 can be appropriately configured based on, for example, dental hygiene considerations.

[0105] The brushing pressure applied by the subject can be measured, for example, by a pressure sensor provided in the toothbrush 2 for measuring brushing pressure. The brush pressure evaluation unit 106 obtains the measured brushing pressure and inputs it into the brush pressure evaluation model 112, thereby calculating an evaluation value for the brushing pressure. For example, if the measured brushing pressure value is transmitted from the toothbrush 2 to the evaluation device 1 at predetermined intervals, the brush pressure evaluation unit 106 can also calculate the evaluation value at predetermined intervals. In this embodiment, the control unit 10 does not necessarily need to include the brush pressure evaluation unit 106, but it is preferred that the control unit 10 include the brush pressure evaluation unit 106.

[0106] Angle evaluation unit 107 calculates an angle evaluation value for the angle of toothbrush 2 used by the subject while brushing. For example, angle evaluation unit 107 can calculate this evaluation value using angle evaluation model 113. Angle evaluation model 113 can also be a function that returns a higher evaluation value for toothbrush 2 angles within the appropriate range and a lower evaluation value for toothbrush 2 angles that deviate further from the appropriate range.

[0107] Figure 88003 in FIG. 1 shows an angle estimation model 113A as an example of the angle estimation model 113. Figure 8 8001 is a schematic diagram illustrating the toothbrush angle, and 8002 is a schematic diagram of an example of the optimal toothbrush angle corresponding to each direction of the toothbrush brush. In addition, the "head" recorded in 8001 represents the appearance observed from directly above the head of the toothbrush user.

[0108] Here, as shown in 8001, the toothbrush angle is defined as 0° when the brush portion (bristles) faces the right side of the user's horizontal line of sight, 90° when the brush portion (bristles) faces the upper side of the user's vertical line of sight, and 180° when the brush portion (bristles) faces the left side of the user's horizontal line of sight. Regardless of the toothbrush angle, the brush portion of the toothbrush is positioned toward the user's front, and the handle is positioned away from the user's front. The toothbrush angle can also be referred to as the brush portion orientation.

[0109] The appropriate toothbrush angle varies depending on the area being brushed and the brushing method. For example, if a person brushes the upper right cheek using a straight brushing method, where the bristles contact the tooth surfaces at a 90° angle, the bristles will be facing the left side of the person. In this case, if the toothbrush angle is controlled within a range of approximately 135° to 225°, it will be easier to keep the bristles in contact with the tooth surfaces at a 90° angle.

[0110] In this way, if the brushing method is determined, the bristle direction and the appropriate toothbrush angle range can be specified for each area of ​​brushing. For example, if the toothbrush user brushes with a straight brush method, the toothbrush can also be adjusted as follows: Figure 8 As shown in 8002 in FIG, the appropriate angle is defined as follows: when the bristles are facing the right side, the appropriate toothbrush angle is 0° to 45° and 315° to 360°; when the bristles are facing the upper side, the appropriate toothbrush angle is 45° to 135°; when the bristles are facing the left side, the appropriate toothbrush angle is 135° to 225°; when the bristles are facing the lower side, the appropriate toothbrush angle is 225° to 315°.

[0111] Next, a function can be generated in which the evaluation values ​​are maximum at the center position of each area and its surrounding areas, and the evaluation values ​​decrease as the distance from the center position increases. This function can be used as the angle evaluation model 113. In this case, the angle evaluation model 113 is generated for each brushing area (or alternatively, for each orientation of the bristles during brushing).

[0112] Figure 8Angle evaluation model 113A shown in Figure 8003 is used to evaluate the angle of the toothbrush 2 in the brushing area opposite the left-facing bristles when brushing with the straight brushing method. According to angle evaluation model 113A, the evaluation value is the highest when the angle of the toothbrush 2 is near 180°, and the evaluation value decreases as it deviates from 180°.

[0113] The method for determining the tilt angle and brushing area is not particularly limited. For example, the angle evaluation unit 107 can calculate the tilt angle of the toothbrush 2 by analyzing triaxial acceleration data measured by an acceleration sensor included in the toothbrush 2. Furthermore, if, for example, a user is prompted to brush by displaying operational guidance information specifying a brushing area, the angle evaluation unit 107 can determine the area specified in the operational guidance information as the brushing area.

[0114] The angle evaluation unit 107 may also calculate the evaluation value of the angle of the toothbrush 2 at each predetermined interval. Figure 8 The angle shown in 8001 can also be the angle of the brush portion relative to the tooth surface.

[0115] As mentioned above, the appropriate angle of the toothbrush varies depending on the brushing method. Figure 9 This is a diagram showing an example of an angle evaluation model used when brushing with the oblique brushing method. The oblique brushing method is a brushing method in which the toothbrush 2 contacts the tooth surface at a 45° angle relative to the tooth surface. Here, the definition of angle is the same as Figure 8 Same as the example.

[0116] For the oblique brushing method, the angle evaluation model 113 can also be generated according to each brushing area (or each direction of the bristles during brushing). Figure 9 As shown in 9001 in FIG, the appropriate angle is defined as follows: when the bristles face the right-upper range, the appropriate toothbrush angle is 0° to 90°; when the bristles face the upper-left range, the appropriate toothbrush angle is 90° to 180°; when the bristles face the left-lower range, the appropriate toothbrush angle is 180° to 270°; when the bristles face the lower-right range, the appropriate toothbrush angle is 270° to 360°.

[0117] Next, a function may be generated in which the evaluation value is the largest at the center position and its peripheral positions of each region and the evaluation value decreases as the distance from the center position increases. This function may be used as the angle evaluation model 113 . Figure 9 Angle evaluation model 113B shown in Figure 9002 is used to evaluate the angle of toothbrush 2 in the area opposite the bristles facing upward and left when brushing with an oblique brushing method. According to angle evaluation model 113B, the evaluation value is the highest when the angle of toothbrush 2 is around 135°, and the evaluation value decreases as it deviates from 135°.

[0118] Here, angle estimation is not limited to the straight brushing method and the oblique brushing method described above, and can be performed for various brushing methods. For example, an angle estimation model 113 corresponding to the brushing method can be prepared in advance. In this case, the angle estimation unit 107 can use the angle estimation model 113 corresponding to the brushing method used by the subject to appropriately perform angle estimation. In this embodiment, the control unit 10 does not necessarily need to include the angle estimation unit 107, but it is preferably included in the control unit 10.

[0119] The comprehensive evaluation unit 108 calculates a comprehensive evaluation value of the subject's brushing based on the evaluation value calculated by the skill evaluation unit 104 and the evaluation value calculated by the time evaluation unit 105. This allows for evaluation that includes not only the index value but also the brushing duration.

[0120] For example, the comprehensive evaluation unit 108 may calculate the sum of the evaluation value calculated by the skill evaluation unit 104 and the evaluation value calculated by the time evaluation unit 105 or their average value as the comprehensive evaluation value.

[0121] In addition, the comprehensive evaluation unit 108 can also calculate the comprehensive evaluation value of the subject's brushing based on the evaluation value calculated by the skill evaluation unit 104, the evaluation value calculated by the time evaluation unit 105, the evaluation value calculated by the brush pressure evaluation unit 106, and the evaluation value calculated by the angle evaluation unit 107. In this way, it is possible to perform an evaluation that also includes the brushing pressure and the angle of the toothbrush 2. In this case, the comprehensive evaluation unit 108 can also calculate the sum of the evaluation values ​​calculated by the skill evaluation unit 104, the evaluation value calculated by the time evaluation unit 105, the evaluation value evaluated by the brush pressure evaluation unit 106, and the evaluation value evaluated by the angle evaluation unit 107, or their average value, as the comprehensive evaluation value. Here, in this embodiment, the control unit 10 does not necessarily need to include the comprehensive evaluation unit 108, but it is preferred that the control unit 10 include the comprehensive evaluation unit 108.

[0122] The display control unit 109 causes the display unit 14 to display the evaluation values ​​calculated using the evaluation model 111. In this case, the display control unit 109 may also cause the display unit 14 to display the evaluation values ​​and various information associated with each evaluation value. The display control unit 109 may display the evaluation values ​​for the entire brushing process after brushing, or may display the evaluation values ​​in real time during the brushing process. In this embodiment, the control unit 10 does not necessarily need to include the display control unit 109, but it is preferred that the control unit 10 include the display control unit 109.

[0123] As described above, the evaluation device 1 includes: (1) an index value calculation unit 102 that calculates an index value representing a brushing amplitude based on acceleration data of the toothbrush 2 while the subject is brushing their teeth; and (2) a skill evaluation unit 104 that uses a brushing skill evaluation model 111 generated based on the correlation between the index value and the plaque removal rate to calculate an evaluation value of the subject's brushing skill based on the index value calculated by the index value calculation unit 102. Thus, in the present invention, brushing skill can be evaluated using the brushing skill evaluation model 111 generated based on the correlation between the index value representing the brushing amplitude and the plaque removal rate.

[0124] [Processing Flow (Calculation of Evaluation Value)]

[0125] based on Figure 10 , the flow of the process of calculating the brushing skill evaluation value by the evaluation device 1 (the method of evaluating the brushing skill) will be described. Figure 10 This is a flowchart of an example of a process for calculating the brushing skill evaluation value. Here, in this process, the scheme of displaying the evaluation value after brushing is explained. Figure 10 Calculation of the evaluation value of the brushing time, calculation of the evaluation value of the brushing pressure, calculation of the evaluation value of the angle, and calculation of the comprehensive evaluation value are also shown in FIG. , but these processes are not essential for calculating the evaluation value of the brushing skill.

[0126] In step S11, the information acquisition unit 101 acquires acceleration data of the subject while brushing their teeth. For example, if the subject brushes for three minutes, the time series of acceleration data measured by the toothbrush 2 during that three-minute period is acquired. In step S12, the index value calculation unit 102 performs preprocessing to remove the gravity component from the acceleration data acquired in step S11.

[0127] Next, in step S13, the index calculation unit 102 calculates an index representing the brushing amplitude using the acceleration data after the gravity component has been removed in step S12. In step S14, the skill evaluation unit 104 calculates an evaluation value of the brushing skill based on the index value calculated in step S13 using the evaluation model 111. For example, if brushing of the entire upper and lower jaw is to be evaluated, the index calculation unit 102 can calculate the evaluation value using a representative value (e.g., the average value or maximum value) among the time-series index values ​​calculated in step S13.

[0128] In step S16, the time evaluation unit 105 calculates an evaluation value for the brushing duration. In step S17, the brushing pressure evaluation unit 106 calculates an evaluation value for the brushing pressure. In step S18, the angle evaluation unit 107 calculates an evaluation value for the angle of the toothbrush 2. The evaluation periods and regions in steps S14, 16, and 18 are common. For example, if the entire period of brushing of the upper and lower jaws is to be evaluated, then steps S14, 16, and 18 will all calculate the evaluation value for the entire period.

[0129] In step S19, the comprehensive evaluation unit 108 averages the evaluation values ​​calculated by the skill evaluation unit 104, the time evaluation unit 105, the brush pressure evaluation unit 106, and the angle evaluation unit 107 to calculate an average value. The average value is then output to the display control unit 109 as a comprehensive evaluation value. Alternatively, the comprehensive evaluation unit 108 may use the sum of the individual evaluation values ​​as the comprehensive evaluation value. In step S20, the display control unit 109 displays the evaluation result calculated in step S19 on the display unit 14.

[0130] Here, each function of the evaluation device 1 can also be realized by a system composed of a plurality of information processing devices, and the devices constituting the evaluation system 100 can be changed as appropriate. Figure 10 The execution subjects of each step shown are not limited to the above examples. Figure 10 Each of the steps shown may be executed by one information processing device, or may be executed by having a plurality of information processing devices share the processing of each step.

[0131] As described above, the brushing skill evaluation method of this embodiment is (1) an evaluation method executed by one or more information processing devices, including: an index value calculation step (step S13) of calculating an index value representing the brushing amplitude based on acceleration data of the toothbrush 2 when the subject is brushing their teeth; and (2) a skill evaluation step (step S14) of calculating an evaluation value of the subject's brushing skill based on the index value calculated in the index value calculation step using a brushing skill evaluation model 111 generated based on the correlation between the index value and the plaque removal rate. Thus, it is possible to evaluate the brushing skill for plaque removal.

[0132] [Example of implementation through software]

[0133] The functions of the evaluation device 1 and the model generation device 4 (hereinafter referred to as "device") can be realized by a program (evaluation program / evaluation model generation program) for causing a computer to function as the device so that each control block in the device (especially each part included in the control unit (10, 40)) can function.

[0134] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The functions described in the above embodiments are realized by executing the program by the control device and the storage device.

[0135] The program may also be recorded on one or more non-transitory computer-readable recording media. The recording medium may be included in the device or not. In the latter case, the program may also be provided to the device via any transmission medium, whether wired or wireless.

[0136] Furthermore, some or all of the functions of each control block may be implemented using logic circuits. For example, integrated circuits incorporating logic circuits that function as each control block are also within the scope of the present invention. Furthermore, the functions of each control block may also be implemented using, for example, a quantum computer.

[0137] Furthermore, each process described in the above embodiments may also be executed by AI (Artificial Intelligence). In this case, the AI ​​may be executed in the control device or in another device (such as an edge computer or cloud server).

[0138] The present invention is not limited to the above-mentioned embodiments, and various changes can be made within the scope of the technical concept described in the specification. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention.

Claims

1. An evaluation device comprising: an index value calculation unit for calculating an index value representing a brushing amplitude based on toothbrush acceleration data of a subject while brushing their teeth; A skill evaluation unit calculates an evaluation value of the subject's brushing skill based on the index value calculated by the index value calculation unit using a brushing skill evaluation model generated based on the correlation between the index value and the plaque removal rate.

2. The evaluation device according to claim 1, The apparatus further comprises: a type identification unit for identifying the type of toothbrush used by the subject; The skill evaluation unit calculates the evaluation value by using an evaluation model corresponding to the recognition result of the type recognition unit from among the plurality of evaluation models generated in advance for each type of toothbrush.

3. The evaluation device according to claim 1 or 2, further comprising: a time evaluation unit that calculates an evaluation value for evaluating a brushing time duration of the subject; A comprehensive evaluation unit calculates a comprehensive evaluation value of the brushing of the subject based on the evaluation value calculated by the skill evaluation unit and the evaluation value calculated by the time evaluation unit.

4. An evaluation method, performed by one or more information processing devices, The assessment method includes: an index value calculation step of calculating an index value representing a brushing amplitude based on toothbrush acceleration data of the subject while brushing their teeth; The skill evaluation step uses a brushing skill evaluation model generated based on the correlation between the index value and the plaque removal rate to calculate an evaluation value of the subject's brushing skill based on the index value calculated in the index value calculation step.

5. A method for generating an evaluation model, performed by one or more information processing devices, The generation method of the evaluation model includes: a formulating step of formulating a correlation between an index value representing a brushing amplitude calculated based on toothbrush acceleration data during brushing and a plaque removal rate of the brushing; The model generation step generates, based on the function obtained by the formulation, an evaluation model for calculating the brushing skill evaluation value according to the index value.

6. The method for generating an evaluation model according to claim 5, wherein: In the formulating step, the correlation between the plaque removal rate calculated for the plurality of areas divided on the surface of each tooth and the index value is formulated.

7. An evaluation program for causing a computer to function as the evaluation device according to claim 1, wherein: This evaluation program is for causing a computer to function as the index value calculation unit and the skill evaluation unit.

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