Toothbrush detection device and method

Abstract

According to the toothbrush detection device and method, a mechanical arm and a carrier platform are used for controlling a to-be-detected toothbrush to execute the tooth brushing process, an image collecting device is used for collecting images in the tooth brushing process, and a processor detects the cleaning force effect of the to-be-detected toothbrush according to image detection to obtain a detection result. The cleaning capacity of the toothbrush to be detected is quantified according to the detection result, and the cleaning effect aiming at the tooth target part is introduced, so that the detection result can reflect the capacity of the toothbrush to be detected for preventing or relieving specific oral diseases. Besides, in the implementation mode of the specification, the whole detection process is standardized, long-term observation and test on a large number of subjects are not needed, the detection efficiency is improved, and the detection cost is reduced.

Description

Technical Field

[0001] This manual relates to the field of equipment testing technology, specifically to a toothbrush testing device and method. Background Technology

[0002] Toothbrushes are the most commonly used oral hygiene tools. Toothbrush cleaning power is a crucial indicator of its effectiveness; high-efficiency cleaning can prevent or alleviate oral diseases. However, current technologies primarily evaluate toothbrush cleaning power based on subjective tester experiences, lacking objective and effective standards. This leads to inconsistent cleaning results, negatively impacting oral health. Summary of the Invention

[0003] To effectively test the cleaning power of toothbrushes and improve the reliability and guidance of toothbrush cleaning effect testing, this specification provides a toothbrush testing device, method, storage medium, and computer program product.

[0004] Firstly, embodiments of this specification provide a toothbrush detection device, comprising:

[0005] A carrier platform, on which a dental model is fixedly placed;

[0006] A robotic arm, the end of which is provided with a clamping mechanism for fixing the toothbrush to be tested, the robotic arm being configured to perform a cleaning process of the toothbrush to be tested on the dental model by executing a predetermined program;

[0007] An image acquisition device is used to acquire first and second images of the dental model before and after cleaning, as well as a first cleaning image of the target area on the dental model after cleaning.

[0008] The processor is configured to determine a first cleaning parameter based on the first dental model image and the second dental model image, determine a second cleaning parameter based on the first cleaning image, determine a third cleaning parameter based on the degree of fit between the cleaning surface of the toothbrush under test and the dental model, and determine the test result of the toothbrush under test based on the first cleaning parameter, the second cleaning parameter and the third cleaning parameter.

[0009] In some embodiments, a pressure sensor is provided below the vehicle platform to detect the force applied by the toothbrush to the dental model, and the robotic arm is configured to control the toothbrush to clean the dental model at a preset pressure.

[0010] In some embodiments, the robotic arm includes a drive mechanism connected to the gripping mechanism, the drive mechanism being used to drive the gripping mechanism to move.

[0011] In some embodiments, the driving mechanism includes a linear driving mechanism and a rotary driving mechanism. The linear driving mechanism is used to drive the toothbrush under test to reciprocate linearly, and the rotary driving mechanism is used to adjust the contact angle between the cleaning surface of the toothbrush under test and the dental model.

[0012] In some embodiments, the target area of ​​the dental model includes the lingual and palatal surfaces of the teeth.

[0013] Secondly, the embodiments of this specification provide a toothbrush detection method, including:

[0014] Acquire a first dental model image and a second dental model image, and determine a first cleaning parameter based on the first dental model image and the second dental model image, wherein the first dental model image represents the dental model image before the toothbrush under test cleans the dental model, and the second dental model image represents the dental model image after the toothbrush under test cleans the dental model;

[0015] After cleaning the dental model, a first cleaning image of the target area on the dental model is obtained, and a second cleaning parameter is determined based on the first cleaning image;

[0016] The third cleaning parameter is determined based on the degree of fit between the cleaning surface of the toothbrush under test and the dental model;

[0017] The test result of the toothbrush under test is determined based on the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter.

[0018] In some embodiments, determining the first cleaning parameter based on the first dental model image and the second dental model image includes:

[0019] Image detection is performed on the first dental mold image to determine the first area of ​​the uncleaned region on the dental mold;

[0020] Image detection is performed on the second dental model image to determine the second area of ​​the uncleaned area on the dental model;

[0021] The first cleaning parameter is determined based on the ratio of the second area to the first area.

[0022] In some embodiments, acquiring a first cleaning image of the target area on the dental mold after cleaning the dental mold, and determining the second cleaning parameters based on the first cleaning image, includes:

[0023] The target area on the second dental model image is segmented to obtain the first clean image;

[0024] Based on the first cleaning image and a pre-set correspondence, the second cleaning parameters are determined. The correspondence includes the relationship between the cleaning degree of the target area and the second cleaning parameters.

[0025] In some embodiments, determining the third cleaning parameter based on the degree of fit between the cleaning surface of the toothbrush being tested and the dental model includes:

[0026] The tongue-palatal fit of the toothbrush under test is determined based on the ratio of the contact area between the cleaning surface of the toothbrush under test and the lingual-palatal surface of the dental model.

[0027] The buccal fit of the toothbrush under test is determined based on the ratio of the contact area between the cleaning surface of the toothbrush under test and the labial / buccal surface of the dental model.

[0028] The contact area ratio between the cleaning surface of the toothbrush under test and the occlusal surface of the dental model is used to determine the occlusal surface fit of the toothbrush under test.

[0029] The third cleaning parameter is determined based on the tongue-palatal surface fit, the labial-buccal surface fit, and the occlusal surface fit.

[0030] In some embodiments, determining the test result of the toothbrush based on the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter includes:

[0031] Obtain the first weighting coefficient of the first cleaning parameter, the second weighting coefficient of the second cleaning parameter, and the third weighting coefficient of the third cleaning parameter;

[0032] Based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter are weighted and fused to obtain the detection result.

[0033] In some embodiments, the method further includes:

[0034] The first duration of the toothbrush under test cleaning the dental model and the second duration of the toothbrush under test cleaning the target area of ​​the teeth on the dental model are obtained.

[0035] A first cleaning time for each tooth is determined based on the first cleaning time and the number of teeth cleaned, and a second cleaning time for the target area of ​​each tooth is determined based on the second cleaning time and the number of teeth cleaned.

[0036] The fourth cleaning parameter is determined based on the ratio between the first cleaning time and the second cleaning time;

[0037] The step of determining the test result of the toothbrush under test based on the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter includes:

[0038] The test result of the toothbrush under test is determined based on the first cleaning parameter, the second cleaning parameter, the third cleaning parameter, and the fourth cleaning parameter.

[0039] Thirdly, embodiments of this specification provide a toothbrush detection device, comprising:

[0040] The first determining module is configured to acquire a first dental model image and a second dental model image, and determine a first cleaning parameter based on the first dental model image and the second dental model image, wherein the first dental model image represents the dental model image before the toothbrush under test cleans the dental model, and the second dental model image represents the dental model image after the toothbrush under test cleans the dental model;

[0041] The second determining module is configured to acquire a first cleaning image of the target area on the dental model after cleaning, and to determine a second cleaning parameter based on the first cleaning image.

[0042] The third determining module is configured to determine a third cleaning parameter based on the degree of fit between the cleaning surface of the toothbrush to be tested and the dental model;

[0043] The result determination module is configured to determine the test result of the toothbrush under test based on the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter.

[0044] In some implementations, the first determining module is configured to:

[0045] Image detection is performed on the first dental mold image to determine the first area of ​​the uncleaned region on the dental mold;

[0046] Image detection is performed on the second dental model image to determine the second area of ​​the uncleaned area on the dental model;

[0047] The first cleaning parameter is determined based on the ratio of the second area to the first area.

[0048] In some implementations, the second determining module is configured to:

[0049] The target area on the second dental model image is segmented to obtain the first clean image;

[0050] Based on the first cleaning image and a pre-set correspondence, the second cleaning parameters are determined. The correspondence includes the relationship between the cleaning degree of the target area and the second cleaning parameters.

[0051] In some implementations, the third determining module is configured to:

[0052] The tongue-palatal fit of the toothbrush under test is determined based on the ratio of the contact area between the cleaning surface of the toothbrush under test and the lingual-palatal surface of the dental model.

[0053] The buccal fit of the toothbrush under test is determined based on the ratio of the contact area between the cleaning surface of the toothbrush under test and the labial / buccal surface of the dental model.

[0054] The contact area ratio between the cleaning surface of the toothbrush under test and the occlusal surface of the dental model is used to determine the occlusal surface fit of the toothbrush under test.

[0055] The third cleaning parameter is determined based on the tongue-palatal surface fit, the labial-buccal surface fit, and the occlusal surface fit.

[0056] In some implementations, the result determination module is configured to:

[0057] Obtain the first weighting coefficient of the first cleaning parameter, the second weighting coefficient of the second cleaning parameter, and the third weighting coefficient of the third cleaning parameter;

[0058] Based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter are weighted and fused to obtain the detection result.

[0059] In some implementations, the result determination module is configured to:

[0060] The first duration of the toothbrush under test cleaning the dental model and the second duration of the toothbrush under test cleaning the target area of ​​the teeth on the dental model are obtained.

[0061] A first cleaning time for each tooth is determined based on the first cleaning time and the number of teeth cleaned, and a second cleaning time for the target area of ​​each tooth is determined based on the second cleaning time and the number of teeth cleaned.

[0062] The fourth cleaning parameter is determined based on the ratio between the first cleaning time and the second cleaning time;

[0063] The test result of the toothbrush under test is determined based on the first cleaning parameter, the second cleaning parameter, the third cleaning parameter, and the fourth cleaning parameter.

[0064] Fourthly, embodiments of this specification provide a storage medium storing computer instructions for causing a computer to execute the methods described in any of the above embodiments. Fifthly, embodiments of this specification provide a computer program product that, when executed, implements the methods described in any of the above embodiments.

[0065] The toothbrush testing device described in this specification utilizes a robotic arm and a carrier platform to control the toothbrush under test to perform the brushing process. An image acquisition device captures images of the brushing process, and a processor analyzes these images to determine the cleaning power of the toothbrush. The cleaning ability of the toothbrush is quantified based on these results. Furthermore, by incorporating cleaning effects targeting specific areas of the teeth, the test results can reflect the toothbrush's ability to prevent or alleviate specific oral diseases. In addition, this specification standardizes the entire testing process, eliminating the need for long-term observation trials on a large number of subjects, thus improving testing efficiency and reducing testing costs. Attached Figure Description

[0066] To more clearly illustrate the specific embodiments or technical solutions in the prior art of this specification, the accompanying drawings used in the description of the specific embodiments or prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this specification. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0067] Figure 1 This is a schematic diagram of the human oral cavity.

[0068] Figure 2 This is a schematic diagram of the human oral cavity and mandible.

[0069] Figure 3 This is a structural block diagram of the toothbrush detection device in some embodiments of this specification.

[0070] Figure 4 These are schematic diagrams of the dental model structure in some embodiments of this specification.

[0071] Figure 5 These are schematic diagrams of the dental model structure in some embodiments of this specification.

[0072] Figure 6 This is a flowchart of a toothbrush testing method in some embodiments of this specification.

[0073] Figure 7 This is a flowchart for determining the first cleaning parameter in the toothbrush testing method of this instruction manual.

[0074] Figure 8This is a schematic diagram of a second dental model in some embodiments of this specification.

[0075] Figure 9 This is a flowchart for determining the second cleaning parameter in the toothbrush testing method of this instruction manual.

[0076] Figure 10 This is a flowchart for determining the third cleaning parameter in the toothbrush testing method of this instruction manual.

[0077] Figure 11 This is a schematic diagram of the toothbrush detection method in some embodiments of this specification.

[0078] Figure 12 This is a flowchart for determining the test results in the toothbrush testing method of this instruction manual.

[0079] Figure 13 This is a structural block diagram of the toothbrush detection device in some embodiments of this specification. Detailed Implementation

[0080] The technical solutions of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification. Furthermore, the technical features involved in the different embodiments of this specification described below can be combined with each other as long as they do not conflict with each other.

[0081] Toothbrushes are the most commonly used oral hygiene tools, and with the development of electronic technology, electric toothbrushes are increasingly replacing ordinary toothbrushes, becoming the preferred choice for teeth cleaning. However, regardless of whether it's a regular or electric toothbrush, the cleaning effect on the oral cavity is an important indicator of its cleaning power. Highly effective cleaning can thoroughly clean the oral cavity and reduce the risk of oral diseases.

[0082] There are many types of oral diseases, and different types of oral diseases occur in different locations. For example, gingivitis refers to lesions that occur around the tooth root and gum line, periodontitis refers to the destruction of periodontal tissues by dental plaque, pit and fissure caries refers to lesions that occur in the pits and fissures of the occlusal surface of teeth, and lingual and palatal caries refers to lesions that occur on the lingual and palatal surfaces of teeth. Therefore, the cleaning power of a toothbrush on specific areas of the mouth directly affects its ability to prevent oral diseases.

[0083] In related technologies, the evaluation and testing of toothbrush cleaning power generally employs human efficacy trials. For example, a certain number of subjects are selected to brush their teeth using the toothbrush under test during the test period, and the cleaning effect is observed to determine the toothbrush's cleaning ability. However, this testing process is costly and time-consuming, making it unsuitable for the product development stage.

[0084] More importantly, there are currently no industry standards in the relevant technologies to evaluate the cleaning effect of toothbrushes on specific areas of the mouth (such as the tongue and palate), which leads to a lack of intuitive and effective guidance for people when choosing toothbrushes, and manufacturers also lack objective testing standards during the research and development stage, resulting in poor product performance.

[0085] Based on the deficiencies of the aforementioned related technologies, this specification provides a toothbrush testing device, method, electronic device, storage medium, and computer program product, which aim to objectively quantify the cleaning ability of a toothbrush, thereby simulating the cleaning effect of a toothbrush product on real human teeth, reflecting the toothbrush's ability to prevent oral diseases, and providing a complete set of testing standards for toothbrush cleaning ability, objectively and efficiently testing the cleaning power of a toothbrush.

[0086] Figure 1 and Figure 2 This shows the distribution of teeth in the human oral cavity, for reference. Figure 1 As shown, the human oral cavity is divided into the upper and lower jaws. The teeth in the upper and lower jaws are distributed in the same way, with each jaw containing 14 teeth except for wisdom teeth. Taking the lower jaw teeth as an example, see... Figure 2 As shown, the side of the molar or premolar closest to the human cheek (or lips) is the labial-buccal surface M1, the side closest to the human tongue (or palate) is the lingual-palatal surface M2, and the surface that contacts the maxillary teeth during biting is the occlusal surface M3. The occlusal surface M3 has pits and fissures M4 distributed on it.

[0087] This specification describes an implementation method that allows for the objective and efficient testing and evaluation of a toothbrush's cleaning ability on teeth (or specific areas of teeth). This reflects the toothbrush's cleaning effect on the user's oral cavity and its ability to prevent or alleviate oral diseases in specific areas. This evaluation standard can serve as an industry-wide standard, providing users with intuitive and efficient guidance when selecting toothbrush products, and also offering objective guidance to manufacturers during the research and development phase. This effectively mitigates risks and creates a closed loop for product iteration.

[0088] In some embodiments, this specification provides a toothbrush detection device. Figure 3 The structural block diagram of the detection device is shown below. Figure 3 The detection device is described.

[0089] like Figure 3As shown, in some embodiments, the toothbrush testing device exemplified in this specification includes a toothbrush 100 to be tested, a dental model 200, a robotic arm 300, an image acquisition device 400, a processor 500, and a carrier platform 600.

[0090] The toothbrush to be tested 100 refers to the toothbrush whose cleaning power needs to be tested and evaluated. The toothbrush to be tested 100 can be a regular toothbrush or an electric toothbrush. This instruction manual does not make any restrictions on this.

[0091] A dental model 200 refers to a standard dental model made of polymer materials that mimics the human oral cavity, and it includes the tooth portion and the gum portion. For example... Figure 4 As shown, the dental model 200 in the embodiments of this specification adopts a standard dental model. The gingiva 1 can be made of polymer material, and the teeth 2 can be made of materials such as zirconium dioxide and composite metal. The gingiva 1 wraps around the teeth 2, completely imitating the structure of the real human oral cavity.

[0092] The carrier platform 600 refers to the platform on the testing device used to fix and place the dental model 200. Before the testing begins, the staff can place the dental model 200 on the carrier platform and fix it with the fixing structure on the platform to prevent the dental model 200 from moving during the brushing process.

[0093] The robotic arm 300 is used to hold the toothbrush 100 to be tested, and the robotic arm 300 can be driven by the processor 500, so that the robotic arm 300 can hold the toothbrush 100 to be tested to clean the dental model 200.

[0094] In some embodiments, the robotic arm 300 may include a clamping mechanism 310 and a driving mechanism 320. The clamping mechanism 310 is used to fix and assemble the toothbrush 100 to be tested, and the driving mechanism 320 refers to the mechanism that drives the clamping mechanism 310 to move the toothbrush 100 to be tested. For example, in one example, the driving mechanism 320 may include a linear driving mechanism and a rotary driving mechanism. The linear driving mechanism is a structure used to drive the clamping mechanism 310 to perform linear motion, such as a lead screw, hydraulic rod, or other mechanism. The rotary driving mechanism is a structure used to drive the clamping mechanism 310 to perform rotational motion, such as a sizing mechanism, gear ring, or other mechanism. It can be understood that through the cooperation of the linear driving mechanism and the rotary driving mechanism, the robotic arm can achieve more than 300 degrees of freedom of movement.

[0095] In some implementations, a software program can be pre-written in the processor 500. When the processor 500 executes the software program, it can send control commands to the robotic arm 300, thereby controlling the robotic arm 300 to drive the toothbrush 100 to clean the dental model 200.

[0096] In some implementations, the robotic arm 300 can be a robotic arm with a memory function. For example, the user can pre-guide the robotic arm 300 to perform a brushing route, so that the robotic arm 300 can automatically record the movement path and automatically repeat the brushing route to complete the brushing process. In this way, the task programming difficulty of the robotic arm 300 can be reduced, and the detection cycle can be greatly shortened.

[0097] In the embodiments described in this specification, the processor 500 can at least control the robotic arm 300 to hold the toothbrush 100 to be tested and complete the "Bass method" process on the dental model 200.

[0098] In the embodiments described in this specification, the specific structure and control principle of the robotic arm 300 can undoubtedly be understood and fully implemented by those skilled in the art by referring to relevant technologies, and will not be described in detail here.

[0099] See Figure 3 As shown, in some embodiments, a pressure sensor 610 may be provided below the carrier platform 600. The function of the pressure sensor 610 is to detect the pressure on the dental model 200 on the carrier platform 600 during the brushing process.

[0100] It is understandable that the cleaning effect of the toothbrush 100 on the dental model 200 will be affected by the pressure between the two. Therefore, in order to better simulate the user's actual brushing process, the pressure applied by the toothbrush 100 to the dental model 200 during brushing should be as close as possible to the user's actual brushing state. The function of the pressure sensor 610 is to detect the pressure applied by the toothbrush 100 to the dental model 200. The pressure sensor 610 is connected to the processor 500, so that during brushing, the processor 500 can control the robotic arm 300 in real time according to the pressure value detected by the pressure sensor 610, thereby keeping the pressure value as constant as possible at the preset pressure. For example, in one example, the preset pressure range can be 100N to 200N, such as 150N.

[0101] The image acquisition device 400 is used to acquire frame images or video streams during the cleaning process of the toothbrush 100 on the dental model 200. The image acquisition device 400 may include one or more industrial cameras, ToF (Time of flight) sensors, depth cameras, infrared cameras, lidar, etc., so as to acquire two-dimensional or three-dimensional image information of the dental model 200 from all directions during the cleaning process.

[0102] In the embodiments described in this specification, the image acquisition device 400 needs to acquire at least images of the dental model 200 before and after cleaning, as well as images of the target areas of the dental model 200 after cleaning. The target area refers to one or more specific areas on the dental model 200, such as the lingual / palatal surface of the teeth, the labial / buccal surface of the teeth, the gingiva, etc. The purpose of acquiring images of the target areas is to determine the cleaning effect on the target areas during the cleaning process, thereby reflecting the ability of the toothbrush 100 under test to prevent or alleviate specific oral diseases, as described in the embodiments below.

[0103] Processor 500 refers to the processing core of the detection device. Processor 500 can be any type of processor with one or more processing cores. It can execute single-threaded or multi-threaded operations, used for parsing instructions to perform operations such as acquiring data, performing logical operations, and sending out processing results.

[0104] In some embodiments, the processor 500 may further include a memory, which may include a non-volatile computer-readable storage medium, such as at least one disk storage device, flash memory device, distributed storage device remotely located relative to the processor, or other non-volatile solid-state storage device. The memory may have a program storage area for storing non-volatile software programs, non-volatile computer-executable programs, and modules, which the processor can call to cause the processor to execute one or more method steps below. The memory may also include a volatile random access storage medium, or a storage portion such as a hard disk, as a data storage area for storing the processing results and data output by the processor.

[0105] In this embodiment, the memory stores computer-readable instructions that can be executed by the processor. When these computer-readable instructions are executed, the processor can perform the toothbrush detection method described in the following embodiment. On the other hand, the memory can also store image data acquired by the image acquisition device 400.

[0106] Based on the above-mentioned testing device, the process of testing the toothbrush 100 to be tested using the testing device will be explained below.

[0107] Before testing, an adhesive needs to be applied to the dental mold 200 to simulate tooth stains, plaque, and other residual stains. For example, in one instance, a water-based mixture of staining agent and thickener can be evenly applied to the surface of the dental mold 200 to realistically simulate residual stains. It should be understood that after applying the adhesive, the dental mold 200 can be left to stand for a preset time to allow the adhesive to adhere better. Alternatively, the dental mold 200 can be dried after application to enhance adhesion and more effectively simulate plaque remaining in the human oral cavity; for example, the dental mold 200 can be dried at 45°C for 5 minutes.

[0108] It is worth noting that the application location of the adhesive on the dental model 200 can be set according to specific testing needs. The adhesive can be applied to all tooth areas or only to certain tooth areas. For example, in one example, the adhesive can be applied to all tooth and gingival areas of the dental model 200. In another example, the adhesive can be applied only to the lingual and palatal surfaces of the teeth on the dental model 200, leaving other areas untouched. In yet another example, the adhesive can be applied only to the occlusal surfaces of the teeth on the dental model 200, leaving other areas untouched. In yet another example, the adhesive can be applied only at the gingival line where the gingiva meets the tooth, leaving other areas untouched. In summary, it can be understood that in the embodiments described in this specification, the process of applying the adhesive to the dental model 200 can be selectively applied according to specific testing needs, and this specification does not impose any restrictions on this.

[0109] Furthermore, dental model 200 is not limited to a full-mouth dental model; it can be, for example... Figure 4 The full-mouth dental model shown can also be a half-mouth dental model including only the maxilla (or mandible), or a partial dental model including only a portion of the teeth. In an exemplary embodiment, see [link to example]. Figure 5 As shown, the dental model 200 includes only a portion of the teeth. The red dye in the figure is the coating applied to the tooth surface to simulate residual stains. It can be seen that in this example, the coating is applied only to the lingual and palatal surfaces of a portion of the teeth.

[0110] After applying the adhesive to the dental mold 200, it can be placed on the carrier platform 600 and fixed in place. The dental mold 200 can be secured to the carrier platform 600 using bolts, baffles, or other structures. After fixing the dental mold 200, the pressure sensor 610 can be initialized, and its reading can be returned to zero.

[0111] Before testing, the image acquisition device 400 can pre-capture a first dental model image of the dental model 200 before cleaning. The first dental model image represents the distribution of deposits on the dental model 200 before it is cleaned by the toothbrush 100 to be tested.

[0112] Then, the operator can assemble the toothbrush 100 to be tested onto the clamping mechanism 310 of the robotic arm 300. If the toothbrush 100 to be tested is an electric toothbrush, the operator can pre-start the toothbrush 100 to be tested and adjust the working speed of the toothbrush 100 to the speed that needs to be tested.

[0113] Meanwhile, staff can pre-configure relevant parameters during the brushing process, such as the movement speed and reciprocating stroke of the toothbrush 100 under test controlled by the robotic arm 300. For example, in one example, the movement speed of the toothbrush 100 under test can be set to 0.1mm / s to 50mm / s, and the reciprocating stroke can be set to -20mm to 20mm. This manual does not impose any restrictions on the specific values.

[0114] Subsequently, the processor 500 controls the robotic arm 300 to drive the toothbrush 100 to perform a brushing process on the dental model 200. In some embodiments, the robotic arm 300 can execute a pre-programmed predetermined program to perform a "Bass brushing" process on the dental model 200. The "Bass brushing technique" is an internationally recognized efficient teeth cleaning method. The Bass brushing technique requires the toothbrush to be tilted at 45° to contact the teeth, and there are detailed regulations regarding the brushing direction and sequence, which can be understood by those skilled in the art without further elaboration in this specification. To enable the toothbrush 100 to perform the Bass brushing technique, the robotic arm 300 can be pre-programmed based on the actions of the Bass brushing technique, so that the processor 500 can control the robotic arm 300 to hold the toothbrush 100 and perform a cleaning operation on the dental model 200 in accordance with the preset actions specified by the Bass brushing technique. For example, the robotic arm 300 can be controlled to hold the toothbrush 100 to be tested and perform a 1-minute (the time can be selected according to the needs and there is no specific limit) Bass brushing on the dental model 200 to complete the cleaning process.

[0115] In some implementations, a certain amount of water can be injected into the brush head of the toothbrush 100 before the cleaning process begins, so as to better simulate the real brushing process. For example, 0.5g of water can be injected evenly into the brush head.

[0116] In some implementations, after the cleaning process is completed, the dental mold 200 can be rinsed with clean water to wash away any adhering substances that have detached from the surface, thus preventing these adhering substances from affecting the algorithm accuracy and providing a data basis for the algorithm in subsequent detection processes.

[0117] In the embodiments of this specification, the evaluation of the cleaning power of the toothbrush under test includes at least the following three dimensions: 1. The overall cleaning effect of the toothbrush under test on the teeth; 2. The cleaning effect of the toothbrush under test on specific parts of the teeth; 3. The degree of fit between the cleaning surface of the toothbrush under test and the dental model.

[0118] The overall cleaning effect of the toothbrush on the teeth can reflect the cleaning effect of the toothbrush on all tooth areas with attached substances. The cleaning effect of the toothbrush on a specific tooth area can reflect the cleaning effect of the toothbrush on a specific area. The degree of fit between the cleaning surface of the toothbrush and the dental model can reflect the contact effect between the toothbrush and the tooth surface during the cleaning process.

[0119] In this embodiment of the specification, after the cleaning process is completed using the detection device, the image acquisition device 400 can acquire images of the dental model 200 again to obtain a second dental model image, that is, the second dental model image represents the image of the dental model 200 after cleaning.

[0120] It can be understood that the first dental model image refers to the image of the dental model 200 before the cleaning operation, and the second dental model image refers to the image of the dental model 200 after the cleaning operation. Therefore, the difference between the two images can be used as the first cleaning parameter. The first cleaning parameter can reflect the effect of the attachment falling off during the cleaning process. By detecting the attachment falling off, the overall cleaning effect of the toothbrush 100 on the dental model 200 can be reflected.

[0121] In this embodiment of the specification, in addition to acquiring the first and second images of the dental model 200 before and after cleaning, the image acquisition device 400 also needs to further acquire the image of the target area on the dental model 200 after cleaning, i.e., the first cleaning image.

[0122] As mentioned above, different types of oral diseases occur in different locations. Evaluating the overall cleaning effect of the dental model 200 alone cannot accurately reflect the cleaning effect of the tested toothbrush 100 on specific areas, and therefore cannot accurately reflect the preventative and alleviating effects of the tested toothbrush 100 on a particular type of oral disease. For example, pit and fissure caries mainly occurs due to lesions caused by bacteria remaining in the pits and fissures on the occlusal surface of teeth. During the testing of the tested toothbrush 100, if the tested toothbrush 100 has a good overall cleaning effect on the dental model 200, removing most of the deposits on the teeth and gums, but has a poor cleaning effect on the pits and fissures, its actual preventative and alleviating effect on pit and fissure caries is poor.

[0123] Based on this, in the embodiments of this specification, in addition to determining the first cleaning parameter based on the dental model images before and after cleaning of the dental model 200, it is also necessary to further obtain the first cleaning image of the target area on the dental model, and determine the second cleaning parameter based on the first cleaning image. The second cleaning parameter can reflect the cleaning effect of the toothbrush 100 to be tested on a specific area on the dental model 200.

[0124] The target area can be any one or more of the dental model areas selected according to specific needs, such as the lingual-palatal surface, occlusal surface, pits and fissures, labial-buccal surface, gingiva, periodontal pockets, etc. The first cleaned image of the target area refers to the image corresponding to that area after cleaning the dental model 200. In some embodiments, the first cleaned image of the target area can be acquired separately by the image acquisition device 400, or it can be obtained by image segmentation of the second dental model image. It can be understood that the second dental model image refers to the image of the dental model 200 after cleaning, which includes the entire dental model, while the first cleaned image refers to the image of the target area on the dental model. Therefore, the second dental model image generally contains the content of the first cleaned image. Thus, image detection can be performed on the second dental model image, and the first cleaned image can be obtained by segmenting the image of the target area from the second dental model image. This will be described in the embodiments below.

[0125] In some embodiments of this specification, the third cleaning parameter can be determined based on the degree of contact between the cleaning surface of the toothbrush 100 and the surface of the dental model 200. It can be understood that the cleaning surface of a toothbrush refers to the surface of the brush head that contacts the user's teeth during brushing, achieving cleaning through friction between the cleaning surface and the tooth surface. Different toothbrush shapes correspond to different cleaning surface shapes. Currently, the mainstream toothbrush head has a curved cleaning surface, which is to better match the arch curvature of human teeth, thereby ensuring that the cleaning surface contacts as much of the tooth surface as possible during brushing. The larger the contact area between the toothbrush cleaning surface and the tooth surface, the larger the area of ​​the tooth surface that can be covered during brushing, indicating a higher degree of contact between the toothbrush cleaning surface and the tooth surface. In the embodiments of this specification, the third cleaning parameter can be characterized by the proportion of the contact area between the cleaning surface of the toothbrush head 100 and the tooth surface, which will be explained in the following embodiments.

[0126] After obtaining the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter, the processor 500 can use a fusion algorithm to fuse the data of the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter to calculate an index parameter that reflects the cleaning power effect of the toothbrush 100 under test. This index parameter is the test result described in this specification.

[0127] In some implementations, weighting coefficients can be pre-set for each parameter, and then the first cleaning parameter, second cleaning parameter, and third cleaning parameter can be fused to obtain the test results for the toothbrush under test. This will be described in detail below.

[0128] The structure and principle of the testing device described above have been explained in the embodiments of this specification. Based on the testing device described above, this specification provides a toothbrush testing method. This testing method can be used to test and evaluate the cleaning power of different toothbrushes or different settings of the same toothbrush. The method process is described below.

[0129] In some embodiments, the toothbrush detection method provided in this specification can be applied to the aforementioned toothbrush detection device, with the processor 500 executing the following method steps. For example... Figure 6 As shown, in some examples, the detection method includes:

[0130] S610. Obtain a first dental model image and a second dental model image, and determine a first cleaning parameter based on the first dental model image and the second dental model image.

[0131] It is understood that in the embodiments of this specification, the toothbrush 100 to be tested is used to clean the dental model 200, so that the overall cleaning ability of the toothbrush 100 to be tested on the dental model 200 can be reflected by comparing the effects before and after cleaning. In some embodiments, image detection technology can be used to determine the difference in effects before and after cleaning, and the first cleaning parameter can be determined by computer vision changes.

[0132] To facilitate clearer image comparison, a certain amount of adhering material can be applied to the dental model 200 before cleaning to simulate uncleaned dirt or residue on the teeth. For example, in some embodiments, an aqueous mixture of staining agent and thickener can be applied to the dental model 200 to simulate residues such as dental plaque.

[0133] In some embodiments, when applying the adhesive to the dental model 200, the entire tooth may be coated, or only a portion of the dental model 200 may be coated. This portion of the coating may include, for example, [specific areas of the dental model 200]. Figure 1 The tooth shown includes one or more of the following areas: the lingual-palatal surface M2, the occlusal surface M3, and the labial-buccal surface M1. These will not be described in detail here.

[0134] After treating the pre-defined tooth areas of the dental model 200 with the coating, the dental model 200 can be cleaned using the toothbrush 100. It should be understood that after applying the coating, the dental model can be allowed to stand for a pre-defined time to allow the coating to adhere better to the teeth. Alternatively, the coating can be dried to enhance adhesion, thereby more effectively simulating residues remaining on teeth in the human oral cavity, especially in pits and fissures.

[0135] In some feasible implementations, the tester can hold the toothbrush 100 under test and clean the dental model 200 using a specific brushing method for a preset time. For example, the "Bass brushing technique" is an internationally recognized highly effective teeth cleaning method. The tester can hold the toothbrush 100 under test and perform a 2-minute Bass brushing process on the dental model 200 to complete the cleaning operation. Of course, it should be understood that the preset time of 2 minutes here is just an example and can be adjusted as needed.

[0136] However, it is understandable that during manual cleaning, the cleaning force and speed are difficult to maintain consistently, which can easily introduce large detection errors, resulting in poor detection accuracy. Therefore, in other embodiments of this specification, such as... Figure 3 The testing device shown can perform cleaning operations on the dental model 200 by controlling the robotic arm 300 to hold the toothbrush 100 to be tested.

[0137] For example, in one instance, the processor 500 controls the robotic arm 300 to hold the toothbrush 100 under test and perform a 2-minute Bass brushing process on the dental model 200 to complete the cleaning operation. Because the robotic arm 300 has high control precision, it is more accurate than the manual cleaning process, resulting in higher accuracy of the subsequent test results.

[0138] In some implementations, the image acquisition device 400 may pre-capture one or more first dental mold images of the dental mold 200 before cleaning. After cleaning is completed, the image acquisition device 400 may again capture one or more second dental mold images of the dental mold 200, thereby obtaining images of the dental mold before and after cleaning.

[0139] It can be understood that the first dental model image refers to the image of the dental model 200 before the cleaning operation, and the second dental model image refers to the image of the dental model 200 after the cleaning operation is completed. Therefore, the difference between the two images can reflect the effect of the attached material removal during the cleaning process. By detecting the effect of the attached material removal, the cleaning effect of the toothbrush 100 on the dental model can be reflected.

[0140] In the embodiments described in this specification, image analysis processing can be performed based on the first dental model image before cleaning and the second dental model image after cleaning to determine the first cleaning parameter of the test result. The first cleaning parameter can reflect the overall cleaning ability of the toothbrush 100 to the teeth from a computer vision perspective. The following is in conjunction with... Figure 7 The implementation method describes the process of determining the first cleaning parameter.

[0141] like Figure 7 As shown, in some embodiments, the toothbrush detection method exemplified in this specification, the process of determining a first cleaning parameter, includes:

[0142] S611. Perform image detection on the first dental model image to determine the first area of ​​the uncleaned area on the dental model.

[0143] S612. Perform image detection on the second dental model image to determine the second area of ​​the uncleaned area on the dental model.

[0144] S613. Determine the first cleaning parameter based on the ratio of the second area to the first area.

[0145] In some embodiments, the image acquisition device 400 can acquire images of the dental model 200 before and after the cleaning process, obtaining a first dental model image A and a second dental model image B. It can be understood that the first dental model image A refers to the image of the dental model 200 before cleaning, and the second dental model image B refers to the image of the dental model 200 after cleaning. The difference between the first dental model image A and the second dental model image B reflects the cleaning effect.

[0146] In some implementations, after acquiring the first dental model image A and the second dental model image B, image processing techniques can be used to perform image matting on the tooth region, retaining only the tooth area in the image, thereby removing irrelevant background and improving computational accuracy. For example... Figure 8 The image effect after the second dental model image B is processed by masking is shown. The second dental model image B only includes the tooth area, and other irrelevant areas are removed.

[0147] In some implementations, the ImageJ image processing tool can be used to process the first dental model image A and the second dental model image B. For example, in one instance, image processing can first be performed on the first dental model image A to determine a first area (area_1) of the uncleaned region on the image. Then, image processing can be performed on the second dental model image B to determine a second area (area_2) of the cleaned region on the image, where the second area (area_2) represents the area of ​​the attached material removed during the cleaning process.

[0148] It can be understood that the first area, area_1, represents the area of ​​the uncleaned area on the tooth, and the second area, area_2, represents the area of ​​the cleaned area. Therefore, the ratio of the second area to the first area (area_2 / area_1) can reflect the cleaning effect on the attached substances during the cleaning process.

[0149] With the first area (area_1) of the uncleaned area constant, a larger ratio indicates a larger second area (area_2) of the removed plaque, signifying a better cleaning effect and stronger cleaning power of the toothbrush against plaque residue. Conversely, a smaller ratio indicates a smaller second area (area_2) of the removed plaque, signifying a poorer cleaning effect and weaker cleaning power of the toothbrush against plaque residue. Therefore, in this embodiment, the ratio of the second area to the first area (area_2 / area_1) can be used as the first cleaning parameter K.

[0150] Of course, those skilled in the art will understand that the calculation process for the first cleaning parameter K is not limited to the Image J image processing method described above. Other suitable image processing methods can also be used, such as neural network models based on deep learning, to predict the first cleaning parameter K. Those skilled in the art can understand and fully implement this by referring to the relevant technologies, and this specification does not impose any restrictions on it.

[0151] S620. After cleaning the dental model, obtain a first cleaning image of the target area on the dental model, and determine the second cleaning parameters based on the first cleaning image.

[0152] As described above, the second cleaning parameter Z reflects the cleaning effect of the toothbrush on a specific area of ​​the tooth, thus reflecting the toothbrush's ability to prevent and alleviate oral diseases in that area. In this embodiment, the specific area of ​​the tooth to be tested is defined as the target area.

[0153] For example, in one case, the target area is the lingual / palatal surface of the teeth. The better the cleaning effect of the tested toothbrush 100 on the lingual / palatal surface, the better the toothbrush 100 is at preventing and alleviating dental caries on the lingual / palatal surface. The following will use the lingual / palatal surface as the target area as an example, combined with... Figure 9 The process for determining the second cleaning parameter is explained.

[0154] like Figure 9 As shown, in some embodiments, the detection method of this specification, the process of determining the second cleaning parameter Z includes:

[0155] S621. Perform image segmentation on the target area in the second dental model image to obtain the first clean image.

[0156] S622. Determine the second cleaning parameters based on the first cleaning image and the pre-set correspondence.

[0157] In some example implementations, the second cleaning parameter Z is used to reflect the ability of the toothbrush 100 to prevent or alleviate oral diseases in the target area. Therefore, the focus of the second cleaning parameter Z is on evaluating the cleaning effect on the target area.

[0158] Combination Figure 3 As shown, after cleaning the dental model 200 through the aforementioned process, an image of the cleaned dental model can be acquired using an image acquisition device 400, such as the aforementioned second dental model image B. In some embodiments, to reduce the computational load of image processing, image detection can be performed based on the aforementioned second dental model image B, cropping only the image of the target tooth region to obtain a first cleaned image C of the target region. For example, if the target region is the lingual / palatal surface, only the image region of the lingual / palatal surface of the tooth can be cropped from the second dental model image B as the first cleaned image C, thereby reusing the aforementioned dental model image to calculate the second cleaning parameter Z without repeating image acquisition.

[0159] In some implementations, the detection, recognition, and image cropping of the tooth target region can be achieved through a deep learning-based neural network model, which will not be elaborated further in this specification.

[0160] It is worth noting that, in the embodiments of this specification, the quantification of the cleaning effect on the target tooth area requires a pre-set correspondence, which includes the correspondence between the cleaning degree of the target tooth area and the second cleaning parameter Z. For example, in one example, this correspondence can be shown in Table 1 below:

[0161] Table 1

[0162] Dental lingual and palatal surface cleanliness Second cleaning parameter Z Effect expression There was no obvious dirt on the surface of the tongue and palate. 0 This indicates an extremely low risk of tooth decay and periodontal disease. The area of ​​dirt on the tongue and palate surface is less than 1 / 3 1 This indicates a lower risk of tooth decay and periodontal disease. 1 / 3 ≤ Palatal surface dirt area < 2 / 3 2 This indicates a higher risk of tooth decay and periodontal disease. 2 / 3 ≤ Palatal surface dirt area < 1 3 This indicates an extremely high risk of tooth decay and periodontal disease.

[0163] Based on the correspondence shown in Table 1 above, after obtaining the first cleaning image C of the target area (e.g., the lingual and palatal surfaces) of the dental model 200, the area of ​​the attached material can be determined by feature analysis of the first cleaning image C based on image processing technology. Then, the corresponding second cleaning parameter Z can be determined by the correspondence described in Table 1.

[0164] For example, in one instance, image processing is performed based on the first clean image C to determine that the area covered by dirt on the palatal surface is less than 1 / 3. By referring to the correspondence described in Table 1, the second clean parameter Z = 1 can be determined.

[0165] Of course, those skilled in the art will understand that the correspondence between the cleanliness of the target tooth area and the second cleaning parameter Z is not limited to the example in Table 1. Those skilled in the art can set it independently according to specific scenarios, and this specification will not elaborate further. Furthermore, the process of image processing for the first clean image C can undoubtedly be understood and fully implemented by those skilled in the art by referring to relevant technologies, and this specification will also not elaborate further.

[0166] S630. Determine the third cleaning parameter based on the degree of fit between the cleaning surface of the toothbrush to be tested and the dental model.

[0167] In the embodiments of this specification, the cleaning surface of the toothbrush to be tested refers to the surface of the toothbrush head that contacts the teeth during brushing. It is generally the surface formed by the ends of the bristles on the brush head. In order to better fit the surface of human teeth, the shape of the cleaning surface of the toothbrush is generally arc-shaped.

[0168] Combination Figure 1 As shown, the human tooth model is a three-dimensional structure, and the degree of fit between the toothbrush and the model reflects the toothbrush's cleaning effectiveness. For example, a high degree of fit between the toothbrush's cleaning surface and the model indicates a larger contact area with the teeth during brushing, thus cleaning a wider area of ​​the oral cavity and resulting in better cleaning. Conversely, a low degree of fit between the toothbrush's cleaning surface and the model indicates a smaller contact area with the teeth during brushing, leading to relatively poorer cleaning.

[0169] In the embodiments described in this specification, the third cleaning parameter X includes the following three dimensions: 1. The degree of contact between the toothbrush cleaning surface and the lingual / palatal surface of the teeth; 2. The degree of contact between the toothbrush cleaning surface and the labial / buccal surface of the teeth; 3. The degree of contact between the toothbrush cleaning surface and the occlusal surface of the teeth. The following is in conjunction with... Figure 10 The process of determining the third cleaning parameter X is explained.

[0170] like Figure 10 As shown, in some embodiments, the detection method exemplified in this specification includes the following process for determining the third cleaning parameter X:

[0171] S631. Determine the tongue-palatal fit of the toothbrush based on the ratio of the contact area between the cleaning surface of the toothbrush and the lingual / palatal surface of the dental model.

[0172] S632. Determine the buccal fit of the toothbrush based on the ratio of the contact area between the cleaning surface of the toothbrush and the buccal surface of the dental model.

[0173] S633. Determine the occlusal fit of the toothbrush based on the ratio of the contact area between the cleaning surface of the toothbrush and the occlusal surface of the dental model.

[0174] S634. Based on the lingual-palatal surface fit, labial-buccal surface fit, and occlusal surface fit, determine the third cleaning parameter.

[0175] In some implementations, the image acquisition device 400 can be used to acquire contact images of the cleaning surface of the toothbrush under test with the lingual, palatal, labial, buccal, and occlusal surfaces of the dental model 200. Then, the processor performs image detection based on the contact images to determine the lingual-palatal surface fit E, the labial-buccal surface fit S, and the occlusal surface fit Y.

[0176] For example, see one example. Figure 11 As shown, Figure 11 Image (a) shows an image of the contact between the cleaning surface of the toothbrush and the labial / buccal surface of the dental model. Figure 11 Image (b) shows an image of the contact between the cleaning surface of the toothbrush and the tongue / palatal surface. It is worth noting that, in the embodiments of this specification, the contact image between the cleaning surface and the dental model may include a two-dimensional planar image or a three-dimensional image. The depth sensor of the image acquisition device 400 can capture depth information, thereby constructing a three-dimensional image of the teeth and the dental appliance 100 to be tested. Those skilled in the art will understand this, and it will not be described in detail here.

[0177] In the embodiments described in this specification, image detection technology can be used to detect the contact image between the cleaning surface of the toothbrush under test and the tongue and palate surfaces. The ratio of the contact surface to the entire cleaning surface is taken as the tongue and palate surface fit degree E. Similarly, the labial and buccal surface fit degree S and the occlusal surface fit degree Y can be obtained respectively. Those skilled in the art can undoubtedly understand and fully implement this method by combining it with the image detection algorithms in related technologies, and this specification will not elaborate further.

[0178] In the embodiments described in this specification, after determining the lingual-palatal surface fit E, the labial-buccal surface fit S, and the occlusal surface fit Y, a fusion algorithm can be used to fuse these three parameters to obtain a third cleaning parameter X. For example, in one example, the third cleaning parameter X is represented as:

[0179] X = aESY (1)

[0180] In formula (1), a represents the preset coefficient. The specific value of the preset coefficient can be selected according to the needs. In the example of formula (1), the third cleaning parameter X represents the product of the tongue-palatal surface fit E, the labial-buccal surface fit S and the occlusal surface fit Y and the preset coefficient a.

[0181] S640. Determine the test result of the toothbrush to be tested based on the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter.

[0182] As mentioned above, the first cleaning parameter K represents the overall cleaning effect of the toothbrush on the dental model, the second cleaning parameter Z represents the cleaning effect of the toothbrush on the target area, and the third cleaning parameter X represents the degree of contact between the toothbrush cleaning surface and the teeth. After obtaining the first cleaning parameter K, the second cleaning parameter Z, and the third cleaning parameter X, the test result M of the toothbrush can be determined by combining the three parameters.

[0183] In some implementations, a weighting coefficient can be pre-set for each cleaning parameter, and then the first cleaning parameter K, the second cleaning parameter Z, and the third cleaning parameter X can be fused to obtain the detection result M. The following describes the process in conjunction with... Figure 12 Please provide an explanation.

[0184] like Figure 12 As shown, in some embodiments, the detection method exemplified in this specification includes the following process for determining the detection result M:

[0185] S641. Obtain the first weight coefficient of the first cleaning parameter, the second weight coefficient of the second cleaning parameter, and the third weight coefficient of the third cleaning parameter.

[0186] S642. Based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter are weighted and fused to obtain the detection result.

[0187] In some implementations, the test result M of the toothbrush under test can be expressed as:

[0188] M = f(K, Z, X) (2)

[0189] In formula (2), f() represents the fusion function, which is used to perform fusion calculations on the first cleaning parameter K, the second cleaning parameter Z, and the third cleaning parameter X.

[0190] In some implementations, corresponding weighting coefficients can be pre-set for the first cleaning parameter K, the second cleaning parameter Z, and the third cleaning parameter X. Then, the first cleaning parameter K, the second cleaning parameter Z, and the third cleaning parameter X are fused according to the weighting coefficients to obtain the detection result M, which can be expressed as:

[0191] M=αK+βZ+ωX (3)

[0192] In formula (3), α represents the first weighting coefficient corresponding to the first cleaning parameter K, β represents the second weighting coefficient corresponding to the second cleaning parameter Z, and ω represents the third weighting coefficient corresponding to the third cleaning parameter D. In the embodiments described in this specification, the specific values ​​of α, β, and ω are not limited. Those skilled in the art can select the appropriate coefficient values ​​according to the specific application scenario, and this specification will not elaborate further on this.

[0193] It is worth noting that in the embodiments of this specification, a test result M is defined for the toothbrush under test. This test result M can not only reflect the oral cleaning ability of the toothbrush under test, but also reflect the ability of the toothbrush under test to prevent or alleviate specific oral diseases by introducing the cleaning effect on the target area of ​​the teeth. This is of guiding significance for the formulation of oral medicine industry standards and for users to choose oral hygiene products.

[0194] For example, in one scenario, toothbrush manufacturers or third-party testing institutions can use the toothbrush testing method described in this specification to test the test result M for each setting of each toothbrush or electric toothbrush, and then label the test result M on the product. On one hand, manufacturers can use the test result M to optimize their products in a closed-loop manner during the R&D stage, preventing substandard products from entering the market and posing uncontrollable risks to the company's brand. On the other hand, when purchasing toothbrush products, consumers can also intuitively understand the product's preventative and alleviating effects on various oral diseases through the labeled test result M, allowing them to choose suitable products.

[0195] As described above, the embodiments in this specification quantify the cleaning ability of the toothbrush under test through test results. Furthermore, by introducing cleaning effects targeting specific areas of the teeth, the test results can reflect the toothbrush's ability to prevent or alleviate specific oral diseases, providing objective and efficient guidance for manufacturers and users and promoting the healthy development of the industry. In addition, the embodiments in this specification standardize the entire testing process, eliminating the need for long-term observation trials on a large number of subjects, thus improving testing efficiency and reducing testing costs.

[0196] Additionally, it should be noted that modern electric toothbrushes often have multiple cleaning modes depending on their function, and different modes offer different cleaning effects. Therefore, when the toothbrush under test (100) is an electric toothbrush, the methods described above in this instruction manual can be used to test each cleaning mode of the electric toothbrush.

[0197] That is, combining Figure 3 As shown, when the robotic arm 300 holds the toothbrush 100 to be tested and cleans the dental model 200, it can adjust the toothbrush 100 to a specific cleaning level. The test result M obtained through the above process is the test result for that cleaning level. When it is necessary to further test other cleaning levels, simply change the cleaning level of the electric toothbrush and repeat the above process. This manual will not elaborate further on this.

[0198] As can be seen from the above, the embodiments in this specification can not only test the cleaning effect of the toothbrush, but also further test different cleaning levels of the toothbrush. The test results are objective, effective, and highly instructive, promoting the healthy development of the industry.

[0199] In some implementations, the detection result M may include not only the first cleaning parameter K, the second cleaning parameter Z, and the third cleaning parameter X mentioned above, but may also introduce a time dimension to determine the fourth cleaning parameter N based on the brushing time.

[0200] For example, in one instance, the fourth cleaning parameter N is defined as the ratio of the brushing time T of the target area of ​​each tooth to the actual total brushing time M of each tooth during the brushing process of the toothbrush on the dental model.

[0201] It is understandable that different toothbrushes have different brush head sizes, so the brushing time for each tooth will vary even with the same total brushing time. In some embodiments of this specification, a fourth cleaning parameter N may be introduced to represent the ratio of the target area of ​​each tooth to the total brushing time of that tooth.

[0202] Specifically, we first obtain the first cleaning time T1 of the toothbrush cleaning the dental model, the second cleaning time T2 of the toothbrush cleaning the target area of ​​the dental model, the number of teeth cleaned n, and the number of teeth simultaneously covered by the toothbrush head m. Then, we can calculate the first cleaning time J for each tooth using m*T1 / n. Next, we can calculate the second cleaning time T for the target area of ​​each tooth using m*T2 / n. Finally, we calculate the fourth cleaning parameter N using the ratio of the first cleaning time T to the second cleaning time J, expressed as:

[0203] N = T / J (4)

[0204] Combining the aforementioned first cleaning parameter K, second cleaning parameter Z, and third cleaning parameter X, in this example, the test result M of the toothbrush under test can be expressed as:

[0205] M = f(K, Z, X, N) (5)

[0206] In formula (5), the fusion function f() can be implemented with reference to the aforementioned implementation method, and will not be described again in this specification.

[0207] In some implementations, considering that the materials used to simulate dental plaque vary, and their adhesion to the tooth surface also differs, the adhesion force L of the plaque can be further included in the fusion function f() to explicitly represent this characteristic during the detection process. For example, in one example, the detection result M of the toothbrush being tested can be expressed as:

[0208]

[0209] In formula (6), K represents the first cleaning parameter, L represents the adhesion force of the adhering material, and K / L represents the overall cleaning effect of the toothbrush on the teeth under the condition of material with adhesion force of L.

[0210] As described above, the embodiments in this specification quantify the cleaning ability of the toothbrush under test through test results. Furthermore, by introducing cleaning effects targeting specific areas of the teeth, the test results can reflect the toothbrush's ability to prevent or alleviate specific oral diseases, providing objective and efficient guidance for manufacturers and users and promoting the healthy development of the industry. In addition, the embodiments in this specification standardize the entire testing process, eliminating the need for long-term observation trials on a large number of subjects, thus improving testing efficiency and reducing testing costs.

[0211] In some embodiments, this specification provides a toothbrush detection device, such as... Figure 13 As shown, the detection device includes:

[0212] The first determining module 10 is configured to acquire a first dental model image and a second dental model image, and determine a first cleaning parameter based on the first dental model image and the second dental model image, wherein the first dental model image represents the dental model image before the toothbrush under test cleans the dental model, and the second dental model image represents the dental model image after the toothbrush under test cleans the dental model;

[0213] The second determining module 20 is configured to acquire a first cleaning image of the target area on the dental model after cleaning the dental model, and determine a second cleaning parameter based on the first cleaning image.

[0214] The third determining module 30 is configured to determine a third cleaning parameter based on the degree of fit between the cleaning surface of the toothbrush to be tested and the dental model.

[0215] The result determination module 40 is configured to determine the test result of the toothbrush under test based on the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter.

[0216] In some implementations, the first determining module 10 is configured to:

[0217] Image detection is performed on the first dental mold image to determine the first area of ​​the uncleaned region on the dental mold;

[0218] Image detection is performed on the second dental model image to determine the second area of ​​the uncleaned area on the dental model;

[0219] The first cleaning parameter is determined based on the ratio of the second area to the first area.

[0220] In some implementations, the second determining module 20 is configured to:

[0221] The target area on the second dental model image is segmented to obtain the first clean image;

[0222] Based on the first cleaning image and a pre-set correspondence, the second cleaning parameters are determined. The correspondence includes the relationship between the cleaning degree of the target area and the second cleaning parameters.

[0223] In some implementations, the third determining module 30 is configured to:

[0224] The tongue-palatal fit of the toothbrush under test is determined based on the ratio of the contact area between the cleaning surface of the toothbrush under test and the lingual-palatal surface of the dental model.

[0225] The buccal fit of the toothbrush under test is determined based on the ratio of the contact area between the cleaning surface of the toothbrush under test and the labial / buccal surface of the dental model.

[0226] The contact area ratio between the cleaning surface of the toothbrush under test and the occlusal surface of the dental model is used to determine the occlusal surface fit of the toothbrush under test.

[0227] The third cleaning parameter is determined based on the tongue-palatal surface fit, the labial-buccal surface fit, and the occlusal surface fit.

[0228] In some implementations, the result determination module 40 is configured to:

[0229] Obtain the first weighting coefficient of the first cleaning parameter, the second weighting coefficient of the second cleaning parameter, and the third weighting coefficient of the third cleaning parameter;

[0230] Based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter are weighted and fused to obtain the detection result.

[0231] In some implementations, the result determination module 40 is configured to:

[0232] The first duration of the toothbrush under test cleaning the dental model and the second duration of the toothbrush under test cleaning the target area of ​​the teeth on the dental model are obtained.

[0233] A first cleaning time for each tooth is determined based on the first cleaning time and the number of teeth cleaned, and a second cleaning time for the target area of ​​each tooth is determined based on the second cleaning time and the number of teeth cleaned.

[0234] The fourth cleaning parameter is determined based on the ratio between the first cleaning time and the second cleaning time;

[0235] The test result of the toothbrush under test is determined based on the first cleaning parameter, the second cleaning parameter, the third cleaning parameter, and the fourth cleaning parameter.

[0236] In some embodiments, this specification provides a storage medium storing computer instructions for causing a computer to perform the methods described in any of the above embodiments.

[0237] In some embodiments, this specification provides a computer program product that, when executed, implements the methods described in any of the above embodiments.

[0238] Obviously, the above embodiments are merely examples for clear illustration and are not intended to limit the embodiments. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all embodiments here. However, obvious variations or modifications derived therefrom remain within the scope of protection created by this specification.

Claims

1. A toothbrush detection apparatus, characterized by, The device comprises: a carrier platform on which a dental model is fixedly placed; a mechanical arm, the end of which is provided with a clamping mechanism for fixing a dental brush to be tested, the mechanical arm being configured to realize the cleaning process of the dental brush to be tested on the dental model by executing a predetermined program; an image acquisition device for acquiring a first dental model image and a second dental model image before and after the cleaning of the dental model, and a first cleaning image of a target part on the dental model after the cleaning of the dental model; a processor configured to determine a first cleaning parameter according to the first dental model image and the second dental model image, determine a second cleaning parameter according to the first cleaning image, determine a third cleaning parameter according to the degree of adhesion of the cleaning surface of the dental brush to be tested to the dental model, and determine a test result of the dental brush to be tested according to the first cleaning parameter, the second cleaning parameter and the third cleaning parameter.

2. The device according to claim 1, wherein a pressure sensor is arranged below the carrier platform, the pressure sensor being used to detect the force applied by the dental brush to be tested to the dental model, and the mechanical arm is configured to control the dental brush to be tested to clean the dental model with a preset pressure.

3. The device according to claim 1, wherein the mechanical arm comprises a driving mechanism connected to the clamping mechanism, the driving mechanism being used to drive the clamping mechanism to move.

4. The device according to claim 3, wherein the driving mechanism comprises a linear driving mechanism and a rotary driving mechanism, the linear driving mechanism being used to drive the dental brush to be tested to move linearly back and forth, and the rotary driving mechanism being used to adjust the adhesion angle of the cleaning surface of the dental brush to be tested to the dental model.

5. The device according to claim 1, wherein the target part of the dental model comprises the lingual and palatal surface of the teeth.

6. A toothbrush detection method, characterized by, The device comprises: acquiring a first dental model image and a second dental model image, and determining a first cleaning parameter according to the first dental model image and the second dental model image, wherein the first dental model image represents the image of the dental model before the cleaning of the dental brush to be tested, and the second dental model image represents the image of the dental model after the cleaning of the dental brush to be tested; acquiring a first cleaning image of a target part on the dental model after the cleaning of the dental model, and determining a second cleaning parameter according to the first cleaning image; determining a third cleaning parameter according to the degree of adhesion of the cleaning surface of the dental brush to be tested to the dental model; determining a test result of the dental brush to be tested according to the first cleaning parameter, the second cleaning parameter and the third cleaning parameter.

7. The method of claim 6, wherein, The determination of the first cleaning parameter according to the first dental model image and the second dental model image comprises: performing image detection on the first dental model image to determine the first area of the uncleaned area on the dental model; performing image detection on the second dental model image to determine the second area of the uncleaned area on the dental model; determining the first cleaning parameter according to the ratio of the second area to the first area.

8. The method of claim 6, wherein, The first cleaning image of the target part on the dental mold after the dental mold is cleaned, and the second cleaning parameter is determined according to the first cleaning image, comprising: Image segmentation is performed on the target part on the second dental mold image to obtain the first cleaning image; Based on the first cleaning image and the pre-set corresponding relationship, the second cleaning parameter is determined, and the corresponding relationship includes the corresponding relationship between the cleaning degree of the target part and the second cleaning parameter.

9. The method of claim 6, wherein, The third cleaning parameter is determined according to the fitting degree of the cleaning surface of the to-be-tested toothbrush and the dental mold, comprising: According to the contact area ratio of the cleaning surface of the to-be-tested toothbrush and the lingual and palatal surface of the dental mold, the lingual and palatal surface fitting degree of the to-be-tested toothbrush is determined; According to the contact area ratio of the cleaning surface of the to-be-tested toothbrush and the labial and buccal surface of the dental mold, the labial and buccal surface fitting degree of the to-be-tested toothbrush is determined; According to the contact area ratio of the cleaning surface of the to-be-tested toothbrush and the occlusal surface of the dental mold, the occlusal surface fitting degree of the to-be-tested toothbrush is determined; Based on the lingual and palatal surface fitting degree, the labial and buccal surface fitting degree and the occlusal surface fitting degree, the third cleaning parameter is determined.

10. The method of claim 6, wherein, The detection result of the to-be-tested toothbrush is determined according to the first cleaning parameter, the second cleaning parameter and the third cleaning parameter, comprising: The first weight coefficient of the first cleaning parameter, the second weight coefficient of the second cleaning parameter and the third weight coefficient of the third cleaning parameter are obtained; Based on the first weight coefficient, the second weight coefficient and the third weight coefficient, the first cleaning parameter, the second cleaning parameter and the third cleaning parameter are weighted and fused to obtain the detection result.

11. The method of claim 6, wherein, Further comprising: The first time length of the to-be-tested toothbrush cleaning the dental mold and the second time length of the to-be-tested toothbrush cleaning the target part of the teeth on the dental mold are obtained; According to the first time length and the number of cleaned teeth, the first cleaning time length of each tooth is determined, and according to the second time length and the number of cleaned teeth, the second cleaning time length of the target part of each tooth is determined; The fourth cleaning parameter is determined according to the ratio between the first cleaning time length and the second cleaning time length; The detection result of the to-be-tested toothbrush is determined according to the first cleaning parameter, the second cleaning parameter and the third cleaning parameter, comprising: The detection result of the to-be-tested toothbrush is determined according to the first cleaning parameter, the second cleaning parameter, the third cleaning parameter and the fourth cleaning parameter.

12. A toothbrush detection apparatus, characterized by Comprising: The first determination module is configured to obtain the first dental mold image and the second dental mold image, and determine the first cleaning parameter according to the first dental mold image and the second dental mold image, wherein the first dental mold image represents the dental mold image before the to-be-tested toothbrush cleans the dental mold, and the second dental mold image represents the dental mold image after the to-be-tested toothbrush cleans the dental mold; The second determination module is configured to obtain the first cleaning image of the target part on the dental mold after the dental mold is cleaned, and determine the second cleaning parameter according to the first cleaning image; a third determination module configured to determine a third cleaning parameter according to a degree of fitting between a cleaning surface of the to-be-tested toothbrush and the dental mold; a result determination module configured to determine a detection result of the to-be-tested toothbrush according to the first cleaning parameter, the second cleaning parameter, and the third cleaning parameter.

13. A storage medium, characterized by computer instructions for causing a computer to perform the method according to any one of claims 6 to 11.

14. A computer program product, characterised in that, The computer program product, when executed, implements the method according to any one of claims 6 to 11. The computer program product, when executed, implements the method according to any one of claims 6 to 11.

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