Oral health management system

Abstract

An oral health management system comprises a toothbrush, the toothbrush is provided with a main body and a brush head, the main body is provided with a tooth brushing end and a handheld end, and a connecting part is arranged on one side of the peripheral surface of the tooth brushing end; the brush head is provided with bristles and a base, the bristles are fixedly arranged on the surface of one side of the base, the base is detachably connected with the connecting part, and the bristles stretch out in the direction away from the connecting part; the plurality of data acquisition ends are arranged around the connecting part and are used for acquiring oral cavity information; the server is arranged at a cloud end and is in communication connection with the toothbrush, and after the oral cavity information is processed through a big data technology, an artificial intelligence big model analyzes the oral cavity information to obtain an analysis result; and the man-machine interaction equipment is in communication connection with the server and sends prompt information according to the analysis result.

Description

Technical Field

[0001] The invention relates to the technical field of toothbrushes, in particular to an oral health management system. Background Art

[0002] As people's health awareness increases, oral health, as an important part of overall health, has received more and more attention. Oral diseases such as caries and periodontitis not only affect the health of the oral cavity itself, but may also lead to systemic health problems such as cardiovascular disease and diabetes. Therefore, regular monitoring and management of oral health has become essential.

[0003] However, traditional oral health monitoring mainly relies on regular dental examinations and lacks daily, autonomous monitoring methods. This situation often leads to oral problems being ignored until obvious symptoms appear and they are not discovered and treated, which increases the complexity and cost of treatment. Therefore, there is an urgent need for an oral health management system that can achieve daily oral health monitoring. Summary of the invention

[0004] In view of the above problems in the prior art, the present application provides an oral health management system that can realize daily oral health monitoring.

[0005] The first aspect of the present application provides an oral health management system, comprising: a toothbrush, wherein the toothbrush has a main body and a brush head, the main body has a brushing end and a hand-held end, and a connecting portion is arranged at one side of the outer peripheral surface of the brushing end; the brush head has bristles and a base, the bristles are fixedly arranged on the surface of one side of the base, and the base is detachably connected to the connecting portion so that the bristles extend in a direction away from the connecting portion; a plurality of data acquisition ends are arranged around the connecting portion for acquiring oral information; a server, wherein the server is arranged in the cloud, and is connected to the toothbrush for communication, and after processing the oral information through big data technology, the oral information is analyzed by an artificial intelligence large model to obtain an analysis result; and a human-computer interaction device, wherein the human-computer interaction device is connected to the server for communication, and issues a prompt message according to the analysis result.

[0006] From the above, by setting multiple data collection terminals around the connection part at the brushing end to obtain oral information, the ability to collect oral information can be improved, so that users can have a more comprehensive understanding of oral information, so that users can more accurately judge the health status of the oral cavity, thereby improving the user experience. In addition, after the server processes and analyzes the oral information through the cloud server, it sends prompt information based on the analysis results through the human-computer interaction device, so that users can obtain disease warning information and life behavior suggestions, thereby realizing daily oral health monitoring and improving user experience.

[0007] As a possible implementation of the first aspect, processing the oral information by using big data technology includes: removing noise from the oral information.

[0008] As described above, by removing the noise in the oral information, it is possible to avoid the influence of invalid data or random abnormal values ​​caused by sensor failure on the accuracy of the oral information.

[0009] As a possible implementation of the first aspect, processing the oral information using big data technology further includes: when the missing ratio of data columns or rows in the oral information exceeds a predetermined ratio, deleting the data.

[0010] As described above, by performing deletion processing when the missing ratio of data columns or rows in the oral information exceeds a predetermined ratio, it is possible to avoid affecting the accuracy of the oral information due to missing data columns or rows.

[0011] As a possible implementation method of the first aspect, processing the oral information through big data technology also includes: when data columns or rows in the oral information are missing, the missing data are filled with the mean or median after statistics, or the missing data are filled by interpolation.

[0012] From the above, by filling in the missing data, the integrity of oral information can be guaranteed and the accuracy of oral information can be improved.

[0013] As a possible implementation manner of the first aspect, the oral information includes at least one of image data, pressure data, temperature data, smell data and biological data in the oral cavity.

[0014] As a possible implementation manner of the first aspect, the odor data has a higher priority than other data and is preferentially transmitted to the server.

[0015] From the above, by giving odor data a higher priority than other data, it can be ensured that the odor data can enter the deep analysis process as soon as possible, thereby achieving rapid feedback.

[0016] As a possible implementation manner of the first aspect, processing the oral information through big data technology also includes: performing time synchronization and spatial alignment on the oral information.

[0017] As described above, by synchronizing the time and aligning the space of the oral information, it is possible to ensure that all types of data are consistent at the same time point and in the same spatial range, thereby facilitating the server to analyze the oral information.

[0018] As a possible implementation manner of the first aspect, the human-computer interaction device includes at least one of a mobile phone, a computer, and a tablet computer.

[0019] From the above, users can obtain disease warning information and / or life behavior suggestions through the machine, computer, and tablet computer, which can facilitate the use of users and improve the user experience. In addition, users can also control the toothbrush and the cloud server through the machine, computer, and tablet computer, which can facilitate the operation and use of users.

[0020] As a possible implementation manner of the first aspect, the prompt information includes disease warning information and / or life behavior suggestions.

[0021] According to a second aspect of the present application, there is provided a toothbrush, comprising: a main body, the main body comprising a toothbrush end and a hand-held end, a connecting portion being arranged at one side of the outer peripheral surface of the toothbrush end; a brush head, the brush head comprising bristles and a base, the bristles being fixedly arranged on a surface of one side of the base, the base being detachably connected to the connecting portion so that the bristles extend in a direction away from the connecting portion; a data acquisition module, the data acquisition module being arranged in the main body, the data acquisition module comprising a plurality of data acquisition terminals, the plurality of data acquisition terminals being fixedly arranged on the toothbrush end, arranged around the connecting portion, and being respectively used to collect different types of data.

[0022] By adopting the above structure, the data acquisition module collects different types of data by setting multiple data acquisition terminals around the connecting part at the brushing end, thereby improving the ability to collect oral information and enabling users to have a more comprehensive understanding of oral information, so that users can more accurately judge the health status of the oral cavity, thereby improving the user experience.

[0023] In addition, the brush head can be easily replaced by detachably connecting the base to the connecting portion. The structure of the brush head can be simplified by fixing the bristles on the surface of one side of the base. By arranging the multiple data acquisition terminals of the data acquisition module at positions surrounding the connecting portion, the multiple data acquisition terminals of the data acquisition module can be conveniently used to collect various data in the oral cavity when the brush head cleans the oral cavity. Moreover, by arranging the multiple data acquisition terminals of the data acquisition module at positions surrounding the connecting portion, it is also possible to avoid affecting the multiple data acquisition terminals when replacing the brush head, reduce the connection structure of the data acquisition terminals, and thus simplify the structure of the toothbrush.

[0024] As a possible implementation manner of the second aspect, the connecting portion is in a groove shape, and the base is in a plate shape, which is adapted to the shape of the connecting portion.

[0025] With the above structure, by setting the connecting part in a groove shape and setting the base in a plate shape, the brush head and the connection structure with the connecting part can be simplified.

[0026] As a possible implementation of the second aspect, the base and the connecting portion are detachably connected by means of a snap connection, a fastening connection, a plug-in connection, or the like.

[0027] As a possible implementation manner of the second aspect, the data acquisition module includes at least one of an image data acquisition submodule, a pressure data acquisition submodule, a temperature data acquisition submodule, an odor data acquisition submodule and a biological data acquisition submodule.

[0028] By adopting the above structure, by setting up an image data acquisition submodule, the surface of all tissue structures in the oral cavity can be scanned to realize data acquisition. By setting up a pressure data acquisition submodule, the pressure on the teeth can be monitored in real time during brushing to evaluate the looseness of the teeth. By setting up a temperature data acquisition submodule, the temperature data of each area or regional point in the oral cavity can be monitored in real time. By setting up an odor data acquisition submodule, the odor data in the oral cavity can be monitored in real time. By setting up a biological data acquisition submodule, the biomarkers (such as bacteria, enzymes) and pH value in the saliva in the oral cavity can be monitored in real time.

[0029] As a possible implementation of the second aspect, the image data acquisition submodule has a first data acquisition terminal, and the temperature data acquisition submodule has a second data acquisition terminal. The first data acquisition terminal and / or the second data acquisition terminal are arranged on the corresponding side of the connecting part set at the brushing end, and are located at a position of the connecting part away from the handheld end.

[0030] By adopting the above structure, by arranging the first data acquisition terminal and the second data acquisition terminal on the side of the connection part away from the handheld terminal, when the brush head is cleaning the oral cavity, the first data acquisition terminal and the second data acquisition terminal can collect data close to the cleaning position of the brush head, thereby improving the accuracy of data collection and the continuity of data collection, and avoiding the first data collection terminal and the second data collection terminal being too far away from the brush head, which affects the collection of oral data.

[0031] As a possible implementation manner of the second aspect, the pressure data acquisition submodule has a third data acquisition terminal, and the third data acquisition terminal is arranged on a surface of the connecting portion facing the brush head.

[0032] With the above structure, by setting the third data acquisition terminal on the surface of the connecting part facing the brush head, when the brush head cleans the oral cavity, the pressure between the brush head and the connecting part can be collected to determine the pressure between the brush head and the teeth. In addition, compared with directly setting the third data acquisition terminal in the brush head, by setting the third data acquisition terminal in the connecting part to detect the pressure between the brush head and the teeth, the structure of the brush head and the toothbrush end can be simplified.

[0033] As a possible implementation of the second aspect, the odor data collection submodule has a fourth data collection terminal, and the fourth data collection terminal is arranged at the brushing end, located at a side of the connecting portion facing the handheld end.

[0034] With the above structure, since the toothbrush end needs to be provided with a connecting portion for installing the brush head at the position where the brush head is provided, the installation space of the toothbrush end at the corresponding position of the connecting portion is small and insufficient to install the fourth data acquisition terminal. Moreover, some toothbrush ends are smaller as they are closer to the end. Therefore, by providing the fourth data acquisition terminal at the position of the connecting portion facing the handheld end, the installation space of the fourth data acquisition terminal can be increased to facilitate the installation of the fourth data acquisition terminal.

[0035] As a possible implementation of the second aspect, the biological data collection submodule has a fifth data collection terminal, and the fifth data collection terminal is arranged at the brushing end, located at a side of the connecting portion facing the handheld end.

[0036] With the above structure, since the brush end needs to be provided with a connection part for installing the brush head at the position where the brush head is provided, the installation space of the brush end at the corresponding position of the connection part is small and insufficient to install the fourth data acquisition terminal. Moreover, some brush ends are smaller as they are closer to the end. Therefore, by providing the fifth data acquisition terminal at the position of the connection part facing the handheld terminal, the installation space of the fifth data acquisition terminal can be increased to facilitate the installation of the fifth data acquisition terminal.

[0037] As a possible implementation manner of the second aspect, the fourth data acquisition terminal and the fifth data acquisition terminal are respectively located on the same side of the toothbrush end and the connecting portion, and on the opposite side of the toothbrush end and the connecting portion.

[0038] With the above structure, the fourth data collection terminal and the fifth data collection terminal are respectively arranged on both sides of the toothbrush end, thereby facilitating the installation and arrangement of the fourth data collection terminal and the fifth data collection terminal.

[0039] The third aspect of the present application provides a control method for controlling the toothbrush described in any one of the second aspect of the present application; comprising: obtaining oral information, the oral information including at least one of image data, pressure data, temperature data, odor data and biological data in the oral cavity; sending the oral information to the cloud, analyzing the oral information, and issuing prompt information based on the analysis results, the prompt information including disease warning information and / or life behavior suggestions.

[0040] As mentioned above, by acquiring the image data, pressure data, temperature data, smell data and biological data in the oral cavity and uploading the data to the cloud, the data can be analyzed continuously and frequently to obtain detailed analysis results to improve the user experience.

[0041] As a possible implementation manner of the third aspect, analyzing the oral information specifically includes analyzing the oral information through an AI model.

[0042] From the above, by analyzing oral information through professionally trained AI models in the cloud, comprehensive, accurate and continuous oral health data can be obtained.

[0043] These and other aspects of the invention will become apparent from the following description of the embodiment(s). BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The following further illustrates the various features of the present invention and the relationship between the various features with reference to the accompanying drawings. The accompanying drawings are all exemplary, some features are not shown in actual proportion, and some drawings may omit the conventional features in the field involved in the present application and are not necessary for the present application, or additionally show the features that are not necessary for the present application. The combination of the various features shown in the accompanying drawings is not intended to limit the present application. In addition, throughout this specification, the same figure numerals refer to the same content. The specific description of the drawings is as follows:

[0045] Figure 1 This is a schematic diagram of the front side orthographic projection structure of the toothbrush in this application;

[0046] Figure 2 for Figure 1 A schematic diagram of the structure of the toothbrush head in a disassembled state;

[0047] Figure 3 for Figure 1 A schematic diagram of a radial cross-section of a middle toothbrush at the brushing end;

[0048] Figure 4 for Figure 1 Schematic diagram of the internal structure of the toothbrush;

[0049] Figure 5It is a schematic diagram of the composition of the data acquisition module;

[0050] Figure 6 This is a schematic diagram of the structure of the oral health management system in this application;

[0051] Figure 7 Flow chart of the control method in this application.

[0052] Description of Reference Numerals

[0053] 10 toothbrush; 100 main body; 110 toothbrush end; 111 connection part; 120 handheld end; 200 brush head; 210 bristles; 220 base; 300 data acquisition module; 310 image data acquisition submodule; 311 first printed circuit board; 312 LED light source; 313 bandpass filter; 314 fiber coupler; 315 optical fiber; 316 optical sensor; 317 Hall sensor; 318 angle sensor; 320 pressure data acquisition submodule; 321 thin film pressure sensor; 330 temperature data acquisition submodule; 331 thermistor; 332 voltage divider resistor; 340 odor data acquisition submodule; 341 gas acquisition terminal; 342 flexible air guide tube; 343 waterproof breathable membrane; 344 odor sensor; 350 biological data acquisition submodule; 351 selective membrane; 352 reaction chamber; 353 microfluidic control chip; 354 ​​one-way valve; 355 biosensor; 360 second printed circuit board; 410 third printed circuit board; 420 microcontroller chip; 430 display screen; 510 fourth printed circuit; 520 lithium battery; 530 charging management chip; 540 voltage regulator; 550 fingerprint switch; 20 server; 600 data processing and analysis module; 610 big data processing submodule; 620 large model analysis submodule; 30 human-computer interaction equipment. DETAILED DESCRIPTION

[0054] The words "first, second, third, etc." or module A, module B, module C and other similar terms in the specification and claims are only used to distinguish similar objects and do not represent a specific ordering of the objects. It is understandable that the specific order or sequence can be interchanged where permitted so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0055] In the following description, the numbers representing the steps, such as S110, S120, etc., do not necessarily mean that the steps must be executed in this manner. If permitted, the order of the previous and next steps can be interchanged, or they can be executed simultaneously.

[0056] The term "comprising" as used in the description and claims should not be interpreted as being limited to what is listed thereafter; it does not exclude other elements or steps. Therefore, it should be interpreted as specifying the presence of the features, integers, steps or components mentioned, but does not exclude the presence or addition of one or more other features, integers, steps or components and groups thereof. Therefore, the expression "a device comprising means A and B" should not be limited to a device consisting of components A and B only.

[0057] References to "one embodiment" or "an embodiment" in this specification mean that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment" or "in an embodiment" appearing in various places in this specification do not necessarily refer to the same embodiment, but may refer to the same embodiment. In addition, in one or more embodiments, the particular features, structures, or characteristics can be combined in any appropriate manner, as would be apparent to one of ordinary skill in the art from this disclosure.

[0058] Below, in conjunction with the accompanying drawings, a possible embodiment of the toothbrush 10 in the present application is exemplarily described.

[0059] Figure 1 It is a schematic diagram of the front side orthographic projection structure of the toothbrush 10 in this application; Figure 2 for Figure 1 A schematic structural diagram of the brush head 200 of the middle toothbrush 10 in a disassembled state; Figure 3 for Figure 1 A schematic radial cross-sectional view of the middle toothbrush 10 at the brushing end 110; Figure 4 for Figure 1 Schematic diagram of the internal structure of the toothbrush 10. Figure 1-Figure 4 As shown, the toothbrush 10 in the present application includes a main body 100, a brush head 200 and a data acquisition module 300. The main body 100 has a toothbrush end 110 and a handheld end 120, and a connecting portion 111 is provided on one side of the outer peripheral surface of the toothbrush end 110. The brush head 200 has bristles 210 and a base 220, and the bristles 210 are fixedly arranged on a side surface of the base 220. The base 220 and the connecting portion 111 are detachably connected so that the bristles 210 extend in a direction away from the connecting portion 111. The data acquisition module 300 is arranged in the main body 100, and the data acquisition module 300 has a plurality of data acquisition terminals, which are fixedly arranged on the toothbrush end 110 and arranged around the connecting portion 111, and are respectively used to collect different types of data.

[0060] From the above, the data acquisition module 300 collects different types of data by setting multiple data acquisition terminals around the connecting part 111 at the brushing end 110, thereby improving the ability to collect oral information and enabling users to have a more comprehensive understanding of oral information, so that users can more accurately judge the health status of the oral cavity, thereby improving the user experience.

[0061] In addition, the brush head 200 can be easily replaced by the detachable connection between the base 220 and the connecting portion 111. By fixing the bristles 210 on the side surface of the base 220, the structure of the brush head 200 can be simplified. By arranging the multiple data acquisition terminals of the data acquisition module 300 at a position surrounding the connecting portion 111, the multiple data acquisition terminals of the data acquisition module 300 can be conveniently used to collect various data in the oral cavity when the brush head 200 cleans the oral cavity. Moreover, by arranging the multiple data acquisition terminals of the data acquisition module 300 at a position surrounding the connecting portion 111, it is also possible to avoid affecting the multiple data acquisition terminals when replacing the brush head 200, reduce the connection structure of the data acquisition terminals, and thus simplify the structure of the toothbrush 10.

[0062] In some embodiments, Figure 2 , Figure 3 As shown, the connection part 111 is in a groove shape, and the base 220 is in a plate shape, which matches the shape of the connection part 111. Thus, by setting the connection part 111 in a groove shape and the base 220 in a plate shape, the brush head 200 and the connection structure with the connection part 111 can be simplified.

[0063] In some embodiments, the base 220 and the connecting portion 111 are detachably connected by means of a snap connection, a fastening connection, a plug-in connection, or the like.

[0064] Figure 5 Schematic diagram of the composition of the data acquisition module 300. In some embodiments, Figure 4 .like Figure 5As shown, the data acquisition module 300 includes at least one of an image data acquisition submodule 310, a pressure data acquisition submodule 320, a temperature data acquisition submodule 330, an odor data acquisition submodule 340, and a biological data acquisition submodule 350. Thus, by setting the image data acquisition submodule 310, the surface layers of all tissue structures in the oral cavity can be scanned to realize data acquisition. By setting the pressure data acquisition submodule 320, the pressure on the teeth can be monitored in real time during the brushing process to evaluate the looseness of the teeth. By setting the temperature data acquisition submodule 330, the temperature data of each area or regional point in the oral cavity can be monitored in real time. By setting the odor data acquisition submodule 340, the odor data in the oral cavity can be monitored in real time. By setting the biological data acquisition submodule 350, the biomarkers (such as bacteria, enzymes) and pH value in the saliva in the oral cavity can be monitored in real time.

[0065] In some embodiments, Figure 3 , Figure 4 As shown, the image data acquisition submodule 310 has a first data acquisition terminal, and the temperature data acquisition submodule 330 has a second data acquisition terminal. The first data acquisition terminal and / or the second data acquisition terminal are arranged on the corresponding side of the connection part 111 of the toothbrush end 110, and are located at a position where the connection part 111 is far away from the handheld end 120. Therefore, by arranging the first data acquisition terminal and the second data acquisition terminal on the side of the connection part 111 far away from the handheld end 120, when the brush head 200 cleans the oral cavity, the first data acquisition terminal and the second data acquisition terminal can collect data near the cleaning position of the brush head 200, thereby improving the accuracy of data collection, improving the continuity of data collection, and avoiding the first data acquisition terminal and the second data acquisition terminal being too far away from the brush head 200, which affects the collection of oral data.

[0066] In some embodiments, Figure 3 , Figure 4 As shown, the pressure data acquisition submodule 320 has a third data acquisition terminal, and the third data acquisition terminal is arranged on the surface of the connecting portion 111 facing the brush head 200. Therefore, by arranging the third data acquisition terminal on the surface of the connecting portion 111 facing the brush head 200, when the brush head 200 cleans the oral cavity, the pressure between the brush head 200 and the connecting portion 111 can be collected to determine the pressure between the brush head 200 and the teeth. In addition, compared with directly arranging the third data acquisition terminal in the brush head 200, by arranging the third data acquisition terminal in the connecting portion 111 to detect the pressure between the brush head 200 and the teeth, the structure of the brush head 200 and the toothbrush end 110 can be simplified.

[0067] In some embodiments, Figure 3 , Figure 4 As shown, the odor data collection submodule 340 has a fourth data collection terminal, which is arranged on the toothbrush end 110 and is located at the side of the connecting portion 111 facing the handheld end 120. Therefore, since the toothbrush end 110 needs to be provided with a connecting portion 111 for installing the brush head 200 at the position where the brush head 200 is provided, the installation space of the toothbrush end 110 at the corresponding position of the connecting portion 111 is small and insufficient to install the fourth data collection terminal. Moreover, some toothbrush ends 110 have smaller dimensions as they are closer to the end. Therefore, by arranging the fourth data collection terminal at the side of the connecting portion 111 facing the handheld end 120, the installation space of the fourth data collection terminal can be increased to facilitate the installation of the fourth data collection terminal.

[0068] In some embodiments, Figure 3 , Figure 4 As shown, the biological data collection submodule 350 has a fifth data collection terminal, which is arranged on the toothbrush end 110 and is located at the side of the connecting portion 111 facing the handheld end 120. Therefore, since the toothbrush end 110 needs to be provided with a connecting portion 111 for installing the brush head 200 at the position where the brush head 200 is provided, the installation space of the toothbrush end 110 at the corresponding position of the connecting portion 111 is small and insufficient to install the fourth data collection terminal. Moreover, some toothbrush ends 110 have smaller dimensions as they are closer to the end. Therefore, by arranging the fifth data collection terminal at the side of the connecting portion 111 facing the handheld end 120, the installation space of the fifth data collection terminal can be increased to facilitate the installation of the fifth data collection terminal.

[0069] In some embodiments, Figure 3 As shown, the fourth data acquisition terminal and the fifth data acquisition terminal are respectively located on the same side of the toothbrush end 110 and the connecting portion 111, and on the opposite side of the toothbrush end 110 and the connecting portion 111. Thus, by arranging the fourth data acquisition terminal and the fifth data acquisition terminal on both sides of the toothbrush end 110, the installation and layout of the fourth data acquisition terminal and the fifth data acquisition terminal are facilitated.

[0070] The present application also provides an oral health management system. Below, in conjunction with the accompanying drawings, a possible embodiment of the oral health management system in the present application is exemplarily described.

[0071] Figure 6 This is a schematic diagram of the structure of the oral health management system in this application. Figure 1-Figure 6As shown, the oral health management system in the present application includes a toothbrush 10, a server 20 and a human-computer interaction device 30. Among them, the toothbrush 10 has a main body 100 and a brush head 200, the main body 100 has a toothbrush end 110 and a handheld end 120, and a connecting portion 111 is arranged on one side of the outer peripheral surface of the toothbrush end 110. The brush head 200 has bristles 210 and a base 220, the bristles 210 are fixedly arranged on the surface of one side of the base 220, and the base 220 is detachably connected to the connecting portion 111, so that the bristles 210 extend in a direction away from the connecting portion 111. A plurality of data acquisition terminals are arranged around the connecting portion 111 for obtaining oral information. The server 20 is arranged in the cloud, and is connected to the toothbrush 10 in communication. After the oral information is processed by big data technology, the oral information is analyzed by the artificial intelligence large model to obtain the analysis result. The human-computer interaction device 30 is connected to the server 20 in communication, and a prompt message is issued according to the analysis result.

[0072] As described above, by arranging a plurality of data collection terminals around the connection portion 111 at the toothbrush end 110 to obtain oral information, the ability to collect oral information can be improved, so that the user can have a more complete understanding of the oral information, so that the user can more accurately judge the health status of the oral cavity, thereby improving the user experience. In addition, after the server 20 processes and analyzes the oral information through the cloud server 20, a prompt message is issued according to the analysis result through the human-computer interaction device 30, so that the user can obtain disease warning information and life behavior suggestions, thereby improving the user experience.

[0073] In some embodiments, processing the oral information by big data technology includes removing noise from the oral information. By removing the noise from the oral information, the influence of invalid data or random abnormal values ​​caused by sensor failure on the accuracy of the oral information can be avoided.

[0074] In some embodiments, processing the oral information by big data technology further includes: when the missing ratio of data columns or rows in the oral information exceeds a predetermined ratio, deleting the data columns or rows. Thus, by deleting the data columns or rows in the oral information when the missing ratio exceeds a predetermined ratio, the accuracy of the oral information can be prevented from being affected by missing data columns or rows.

[0075] In some embodiments, processing oral information by big data technology also includes: when data columns or rows in the oral information are missing, using the mean or median to fill the missing data after statistics, or filling the missing data by interpolation. Thus, by filling the missing data, the integrity of the oral information can be guaranteed and the accuracy of the oral information can be improved.

[0076] In some embodiments, the oral information includes at least one of image data, pressure data, temperature data, smell data and biological data within the oral cavity.

[0077] In some embodiments, the smell data has a higher priority than other data and is transmitted to the server 20 first. Thus, by giving the smell data a higher priority than other data, it is possible to ensure that the smell data can enter the deep analysis process as soon as possible, thereby achieving rapid feedback.

[0078] In some embodiments, processing oral information by big data technology also includes: performing time synchronization and spatial alignment on the oral information. Thus, by performing time synchronization and spatial alignment on the oral information, it is possible to ensure that various types of data are consistent at the same time point and within the same spatial range. Thus, it is convenient for the server 20 to analyze the oral information.

[0079] In some embodiments, the human-computer interaction device 30 includes at least one of a mobile phone, a computer, and a tablet computer. Thus, the user can obtain disease warning information and / or life behavior suggestions through the machine, computer, or tablet computer, thereby facilitating the use of the user and improving the user's experience. In addition, the user can also control the toothbrush 10 and the cloud server 20 through the machine, computer, or tablet computer, thereby facilitating the user's operation and use.

[0080] In some embodiments, the prompt information includes disease warning information and / or life behavior suggestions.

[0081] The above content is an exemplary description of possible embodiments of the toothbrush 10 and the control system of the toothbrush in the present application. Next, the specific structure of the toothbrush 10 in the present application is described in detail in a specific embodiment.

[0082] like Figure 1-Figure 5 As shown, the toothbrush 10 in the embodiment of the present application includes a main body 100, a brush head 200, a data acquisition module 300, a chip module and a power module. The main body 100 is used to accommodate and install the brush head 200, the data acquisition module 300, the chip module and the power module. The brush head 200 is used to clean the teeth when the user is brushing the teeth. The data acquisition module 300 is used to collect data in the user's mouth when the user is brushing the teeth. The chip module is used to receive, process and transmit the data collected by the data acquisition module 300. The power module is used to provide power to the toothbrush 10.

[0083] like Figure 1-Figure 3As shown, the main body 100 is a cylindrical structure as a whole. In the upright state, the lower half of the main body 100 is the handheld end 120, and the upper half is the toothbrush end 110. The diameter of the handheld end 120 is large, so it is convenient for the user to hold it when brushing teeth. The diameter of the toothbrush end 110 is small, so it is convenient to insert it into the user's mouth for cleaning. The toothbrush end 110 is flat at a position away from one end of the handheld end 120, and a concave connecting portion 111 is provided on a side plane for connecting the brush head 200.

[0084] like Figure 1 , Figure 2 As shown, the brush head 200 includes a base 220 and bristles 210. The base 220 is an oblong plate-shaped component, and the bristles 210 are vertically arranged on the base 220 and cover one side surface of the base 220. The shape and size of the connecting portion 111 are adapted to the base 220, and the base 220 can be embedded in the connecting portion 111. The base 220 and the connecting portion 111 are detachably connected through a snap-fit ​​structure.

[0085] like Figure 5 As shown, the data acquisition module 300 includes at least one of an image data acquisition submodule 310, a pressure data acquisition submodule 320, a temperature data acquisition submodule 330, an odor data acquisition submodule 340, and a biological data acquisition submodule 350. Thus, by setting the image data acquisition submodule 310, the surface layers of all tissue structures in the oral cavity can be scanned to realize data acquisition. By setting the pressure data acquisition submodule 320, the pressure on the teeth can be monitored in real time during the brushing process to evaluate the looseness of the teeth. By setting the temperature data acquisition submodule 330, the temperature data of each area or regional point in the oral cavity can be monitored in real time. By setting the odor data acquisition submodule 340, the odor data in the oral cavity can be monitored in real time. By setting the biological data acquisition submodule 350, the biomarkers (such as bacteria, enzymes) and pH value in the saliva in the oral cavity can be monitored in real time.

[0086] Next, the relevant contents of the image data acquisition submodule 310 , the pressure data acquisition submodule 320 , the temperature data acquisition submodule 330 , the odor data acquisition submodule 340 and the biological data acquisition submodule 350 are described in detail.

[0087] Image data acquisition submodule 310

[0088] The image data acquisition submodule 310 includes a first printed circuit board 311 , an LED light source 312 , a bandpass filter 313 , a fiber coupler 314 , an optical fiber 315 , an optical sensor 316 , a Hall sensor 317 , and an angle sensor 318 .

[0089] The first printed circuit board 311 includes a power management unit for adjusting the input voltage to provide a stable power supply for the image data acquisition submodule 310, and stably powering the LED light source 312 and other electronic components. The first printed circuit board 311 is embedded in the handheld end 120 of the toothbrush 10. The first printed circuit board 311 adopts a multi-layer design, such as a three-layer design, the top layer is used to transmit power and part of the signal, the second layer is dedicated to grounding, reducing electromagnetic interference, and providing a unified grounding point. The third layer is dedicated to power distribution and provides a stable power supply. The LED light source 312 with a specific wavelength in the range of 660nm-750nm is connected to the first printed circuit board 311 through a MOSFET (metal oxide semiconductor field effect transistor) drive circuit to provide power and control signals. The multi-spectral optical sensor 316 is connected to the first printed circuit board 311 through the VCC pin to obtain the required power. The Hall sensor 317 and the angle sensor 318 are connected to the first printed circuit board 311 through a flexible flat cable (FFC / FPC) and a ZIF connector to ensure its stable power supply. Connected to a common power module through a power management module to ensure a stable power supply.

[0090] The LED light source 312 is used to emit light of a specific wavelength, specifically, to emit light of a specific wavelength in the range of 660nm-750nm, for intraoral image data acquisition. The power of 5mW is sufficient to penetrate oral fluids and is highly safe. The size of the LED light source 312 is miniaturized and suitable for installation inside the handle of the toothbrush 10. The LED light source 312 is connected to the first printed circuit board 311 through a light source driving circuit to provide power and control signals. A bandpass filter 313 is installed at the output end of the red light source to ensure the purity of the light.

[0091] The bandpass filter 313 is used to filter light of a specific wavelength to ensure that the light emitted by the light source is pure. The bandpass filter 313 is required to be suitable for matching the selected wavelength. The bandpass filter 313 adopts a miniaturized design and is suitable for installation inside the handle of the toothbrush 10. The bandpass filter 313 is encapsulated with high-temperature resistant and moisture-proof materials, and a waterproof coating is added to the surface to increase durability and stability. The transmission path (output path) connection mode of the bandpass filter 313 is that the bandpass filter 313 is installed at the output end of the LED light source 312 and is physically fixed to the light source to ensure the purity of the light and filter the light of a specific wavelength. The receiving path (input path) connection mode of the bandpass filter 313 is that the bandpass filter 313 is installed at the input end of the optical fiber coupler 314 to receive the reflected light. Ensure that the reflected light is pure and filter the light of a specific wavelength.

[0092] The fiber coupler 314 is used to guide the light output by the LED light source 312 into the optical fiber 315 to ensure accurate transmission of the light. The fiber coupler 314 of the receiving path is used to accurately connect the optical signal transmitted by the optical fiber 315 to the input end of the multi-spectral optical sensor 316. The fiber coupler 314 adopts a miniaturized design and is suitable for installation inside the handle of the toothbrush 10. The transmission path connection method is that the fiber coupler 314 is connected to the output end of the filter and is connected to the interface of the optical fiber 315. The receiving path connection method of the fiber coupler 314 is that the input end of the fiber coupler 314 is connected to the output end of the bandpass filter 313. The output end of the fiber coupler 314 accurately transmits the reflected light to the signal input end of the multi-spectral optical sensor 316.

[0093] The optical fiber 315 is used to transmit, transmit and receive light. The optical fiber 315 has a shielding cover wrapped in the outermost layer to prevent external light interference. The diameter of the optical fiber in the optical fiber 315 and the diameter of the cladding (shielding cover) are suitable for installation inside the handle of the toothbrush 10. The shielding cover is made of black material. The transmission path connection mode of the optical fiber 315 is that the optical fiber 315 is connected to the optical fiber coupler 314 through the optical fiber 315 adapter, extending to the toothbrush end 110 of the toothbrush 10 to ensure stable transmission of light. The end of the optical fiber 315 is located on the upper side of the connecting part 111 (away from the handheld end 120), forming a first data acquisition terminal. The receiving path connection mode of the optical fiber 315 is to connect the output end of the optical fiber 315 to the input end of the bandpass filter 313. Ensure that the bandpass filter 313 is firmly fixed to the output end of the optical fiber 315 to prevent movement or loosening.

[0094] The optical sensor 316 is used to efficiently receive the light reflected from the toothbrush end 110 and convert it into an electronic signal so as to collect light reflection data of various tissue surfaces in the oral cavity during the toothbrushing process. The optical sensor 316 is used to capture the reflection information of a light source of a specific wavelength and is designed to be miniaturized. The optical sensor 316 is installed in the handheld end 120 of the toothbrush 10 to ensure effective connection and signal transmission. The optical sensor 316 is fixed using a suitable fixing method, such as gluing or screws, to ensure the stability and reliability of the sensor during the toothbrushing process. The power supply connection method of the optical sensor 316 is that the optical sensor 316 is connected to the first printed circuit board 311 through the VCC pin to obtain power, and the GND pin of the optical sensor 316 is connected to the GND pin of the first printed circuit board 311 to ensure stable operation of the sensor. The optical sensor 316 is connected to the chip module through the I2C interface.

[0095] The Hall sensor 317 and the angle sensor 318 are used to detect the position and angle of the toothbrush end 110 of the toothbrush 10, generate position and angle data, and provide spatial marking for data collection. The Hall sensor 317 and the angle sensor 318 are both miniaturized and installed in the toothbrush end 110, located at the rear position of the connecting part 111, close to the area (brush head 200) where the position and angle changes need to be monitored. The Hall sensor 317 and the angle sensor 318 use a suitable fixing method, such as gluing or screws, to ensure the stability and reliability of the sensor during the toothbrush brushing process. The power supply connection method of the Hall sensor 317 and the angle sensor 318 is that the Hall sensor 317 and the angle sensor 318 are connected to the first printed circuit board 311 of the image data acquisition submodule 310 through a flexible flat cable (FFC / FPC) to obtain power. Ensure the stable operation of the Hall sensor 317 and the angle sensor 318. The signal processing connection mode of the Hall sensor 317 and the angle sensor 318 is that the Hall sensor 317 is connected to the chip module through the GPIO interface, and the angle sensor 318 is connected to the chip module through the ADC interface.

[0096] During the brushing process, the image data acquisition submodule 310 uses a specific wavelength LED light source 312 in the selected wavelength range of 660nm-750nm to perform high-resolution scanning of shallow tissues such as teeth, gums, tongue, and the inner wall of the mouth through reflected light intensity measurement and spectral analysis. The data collected by the optical sensor 316 and the data collected by the Hall sensor 317 and the angle sensor 318 are uploaded to the cloud through the chip module built into the toothbrush 10. After processing, the data can provide basic data for the professionally trained AI model to generate a comprehensive digital image model of the oral cavity, and the data will be timestamped when passing through the chip module. At the same time, these data can also provide the position basis for collecting data in the oral cavity for the pressure data acquisition submodule 320 and the temperature data acquisition submodule 330. During the brushing process, the toothbrush 10 will move at multiple angles and multiple positions in the oral cavity. Using this action characteristic, data from various parts of the oral cavity can be gradually collected through multiple brushing behaviors. The randomness and diversity of each brushing action allows a single brushing to cover most of the superficial tissues in the mouth. Assuming that a single brushing covers about 70% of the area in the mouth, such as the first brushing (70% coverage), the second brushing (1-(1-0.7)^2≈91% coverage), the third brushing (1-(1-0.7)^3≈97.3% coverage), and the fourth brushing (1-(1-0.7)^4≈99.2% coverage), 4-6 brushings can basically achieve full coverage of all surface tissues in the mouth. The collected data is processed by the chip module and transmitted to the cloud, which can provide the original intraoral image data for the cloud AI model so that the AI ​​model can generate a comprehensive intraoral digital image model.

[0097] The data acquisition and power input and management process of the image data acquisition submodule 310 is as follows: inside the handheld end 120 of the toothbrush 10, an LED light source 312 emitting a specific wavelength in the range of 660nm-750nm is used, and the optical power is within 5mW to ensure that the light can penetrate the mixed liquid produced when brushing teeth in the oral cavity and be used safely. The LED light source 312 is connected to the first printed circuit board 311 through the light source driving circuit to provide power and control signals. The light passes through the bandpass filter 313 installed at the front end of the light source to ensure that only light of a specific wavelength passes. Then the light is transmitted to the optical fiber through the fiber coupler 314 and the optical fiber 315 adapter. The optical fiber is wrapped in a shielding cover made of black material to ensure that the light is stably transmitted to the end of the optical fiber 315 located at the brushing end 110 (the first data acquisition end). The reflected light enters the bandpass filter 313 through the optical fiber collection end face (the first data acquisition end) to ensure that only light of a specific wavelength passes. Then the pure light signal is transmitted to the optical sensor 316 through the fiber coupler 314. The optical sensor 316 is capable of capturing light signals in the range of 660nm-750nm. The multispectral optical sensor 316 is connected to the ESP via an I2C interface, with SDA connected to GPIO 21 and SCL connected to GPIO 22 to ensure accurate data collection and processing. The Hall sensor 317 and the angle sensor 318 are used to detect the position and angle of the toothbrush 10 head, generate position and angle data, and provide spatial markers for data collection. The signal pin of the Hall sensor 317 is directly connected to the GPIO 19 interface of the ESP via a flexible flat cable. The analog signal pin of the angle sensor 318 is directly connected to the ADC pin (GPIO 34, ADC1_CH6) of the ESP via a flexible flat cable to ensure data collection and processing. In order to ensure that the optical system design is suitable for light sources in the range of 660nm-750nm, the following is a detailed light attenuation calculation process and an analysis of the final results, with an initial light intensity of 5mW.

[0098] The insertion loss of the bandpass filter 313 is 0.3dB (average value)

[0099]

[0100] I1=5mW×0.933=4.665mW

[0101] The insertion loss of the fiber coupler 314 is also 0.3 dB (average value)

[0102]

[0103] I2=4.665mW×0.933=4.351mW

[0104] The total length of the output and input of the optical fiber 315 is about 10 cm (0.1 m), and the loss of the optical fiber 315 is 0.3 dB / m (average value).

[0105]

[0106] I3=4.351mW×10 -0.003

[0107] I3=4.351mW×0.993=4.319mW

[0108] Absorption coefficient of mixed liquid in the mouth: Water, absorption coefficient is about 1.25m-1. Toothpaste (main ingredient is silicon dioxide), absorption coefficient is about 5m-1. Saliva, absorption coefficient is about 1.5m-1. The mixing ratio is 30% water, 50% toothpaste, 20% saliva (since the ratio of ingredients will change during brushing, take the average value)

[0109] α 混合 =0.3×1.25+0.5×5+0.2×1.5=0.375+2.5+0.3=3.175m -1

[0110] Assume the maximum thickness of the mixed liquid is 0.5 cm (0.005 m)

[0111]

[0112] I4=4.319mW×10 -0.0015875

[0113] I4=4.319mW×0.9963=4.303mW

[0114] Oral surface reflection, tooth surface reflectivity is set to 40%, Rteeth = 0.4

[0115] I teeth =I4×R teeth

[0116] I teeth =4.303mW×0.4=1.721mW

[0117] The reflectivity of the soft tissue surface is assumed to be 15%. Rtissue = 0.15

[0118] I tissue =I4×R tissue

[0119] I tissue =4.303mW×0.15=0.645mW

[0120] Pass through the mixed liquid again

[0121]

[0122] I5=I teeth / tissue ×0.9963

[0123] For tooth reflexes:

[0124] I5=1.721mW×0.9963=1.715mW

[0125] For soft tissue reflexes:

[0126] I5=0.645mW×0.9963=0.643mW

[0127] The return optical fiber 315 has a loss. The length of the return optical fiber 315 is within 9 cm (0.09 m). The loss of the optical fiber 315 is 0.3 dB / m.

[0128]

[0129] I6=I5×10 -0.027

[0130] I6=I5×0.94

[0131] For tooth reflexes:

[0132] I6=1.715mW×0.94=1.613mW

[0133] For soft tissue reflexes:

[0134] I6=0.643mW×0.94=0.605mW

[0135] The loss through the fiber coupler 314 of the signal input path is 0.3 dB.

[0136]

[0137] I7=I6× 0.933

[0138] For tooth reflexes:

[0139] I7=1.613mW×0.933=1.505mW

[0140] For soft tissue reflexes:

[0141] I7=0.605mW×0.933=0.564mW

[0142] The loss percentages are: tooth reflection path, initial light intensity: 5mW final light intensity: 1.505mW, and the loss percentage is 69.9%. Soft tissue reflection path, initial light intensity: 5mW final light intensity: 0.564mW, and the loss percentage is 88.72%. Despite the high loss, the high-sensitivity multi-spectral optical sensor 316 can still detect the reflected signal from the final light intensity: tooth reflection path: 1.505mW, soft tissue reflection path: 0.564mW, so data collection can still be performed effectively. During the brushing process, the proportion of mixed liquids in the mouth will change, as well as the toothpaste particles and the generated foam, which will affect the absorption coefficient, scattering effect, and reflectivity. Therefore, the collected data can be enhanced by the professionally trained AI model in the cloud through the use of image processing algorithms, which can enhance the signal, reduce noise, and improve the contrast and clarity of the image.

[0143] The power supply of the image data acquisition submodule 310 is provided by an independent first printed circuit board 311. The power input interface of the first printed circuit board 311 is connected to an external power supply to provide stable power input. The power input interface adopts a standard 2.54mm pin header interface, which is connected to an external power supply to provide a stable power input for the first printed circuit board 311. The interface is located on one side of the first printed circuit board 311, which is convenient for connecting to an external power supply. The power management chip is responsible for adjusting the input voltage, ensuring the stability of the output voltage, and avoiding the influence of voltage fluctuations on the system. The chip is configured near the power input interface to ensure the effectiveness of voltage regulation. The light source driving circuit adopts a metal oxide semiconductor field effect transistor to control the switch of the specific wavelength LED light source 312 in the range of 660nm-750nm to ensure its stable operation. The driving circuit is located near the connection point of the LED light source 312 to reduce power transmission loss. The multi-spectral optical sensor 316 is connected to the first printed circuit board 311 through the VCC pin and the GND pin to obtain the required power and ensure that the signal transmission path is short and stable. The Hall sensor 317 and the angle sensor 318 are connected to the first printed circuit board 311 through the VCC pin and the GND pin, and are located at the edge of the first printed circuit board 311 to facilitate connection with the sensor, reduce wiring complexity, and ensure its stable power supply.

[0144] Pressure data acquisition submodule 320

[0145] The pressure data acquisition submodule 320 is connected to the second printed circuit board 360, and includes a thin film pressure sensor 321 (third data acquisition terminal). The thin film pressure sensor 321 is arranged at the bottom of the groove of the connecting part 111 of the toothbrush end 110, and detects the stress condition of the teeth by detecting the pressure between the brush head 200 and the connecting part 111. Specifically, the thin film pressure sensor 321 is connected to the second printed circuit board 360 through a standard I2C interface or a 0.1-inch pin header. It is connected to the chip module through an ADC interface. The thin film pressure sensor 321 is used to collect tooth force data at a high frequency, and can collect data at a frequency of more than 100 times per second to ensure real-time monitoring of tooth force conditions.

[0146] The second printed circuit board 360 includes a power management unit for adjusting the input voltage to provide a stable power supply for the pressure data acquisition submodule 320, and at the same time stably providing power input and management for the odor data acquisition submodule 340. The biological data acquisition submodule 350 and the pressure data acquisition submodule 320 are embedded in the handheld end 120 of the toothbrush 10, and the size is limited to about 30mm x 10mm to meet the miniaturization requirements. The second printed circuit board 360 adopts a three-layer design, including a transmission power layer and a ground layer, and the bottom layer is used for power distribution to improve the stability of the power supply and signal and reduce electromagnetic interference. The second printed circuit board 360 is connected to an external power supply through a standard 2.54mm pin header interface. The thin film pressure sensor 321, the odor sensor 344, and the biosensor 355 are connected to the second printed circuit board 360 through a standard I2C interface or a 0.1-inch pin header to obtain power.

[0147] During the brushing process, the thin film pressure sensor 321 monitors the pressure on the teeth in real time and converts it into an electrical signal. The thin film pressure sensor 321 captures pressure data of different parts by detecting pressure changes. These data will be transmitted to the chip module built into the toothbrush 10. In the chip module, the pressure data will be timestamped and spatially marked in combination with the location information of the image data acquisition. In this way, the pressure data is combined with the image data of the specific location in the mouth, so that the cloud AI model can comprehensively analyze these data. Through the cloud AI model, advanced algorithms are used to filter and smooth the data for noise, extract key features, and combine the image data with location information to generate the final analysis results. In this way, the system can effectively evaluate the looseness of teeth, and through this real-time monitoring and data integration, accurately analyze and prevent problems such as loose teeth.

[0148] Temperature data acquisition submodule 330

[0149] The temperature data acquisition submodule 330 includes a thermistor 331 (second data acquisition terminal), a voltage divider resistor 332 and a voltage divider circuit. Among them, the thermistor 331 is embedded in the brushing end 110, located on the side of the connecting part 111 away from the handheld end 120, and collects temperature data of various areas and points in the oral cavity in real time during the brushing process, and reflects the temperature change through the change of resistance value. The voltage divider resistor 332 is set in the handheld end 120, and is connected in series with the thermistor 331 probe to form a voltage divider circuit. The voltage divider circuit converts the resistance change of the thermistor 331 into a voltage change, and transmits the voltage signal to the ADC interface of the chip module through a flexible cable (FPC).

[0150] During the brushing process, the temperature acquisition submodule monitors the temperature data of each area or regional point in the oral cavity in real time. After data collection, these data will be processed by the chip module in the toothbrush 10, including adding timestamps and spatial markers. Spatial marking is based on the location information of image data collection to ensure that the temperature data corresponds to the image data at a specific location in the oral cavity. These data are then transmitted to the data storage module and then sent to the cloud through the data transmission module. In the cloud, the AI ​​model will combine the location basis of temperature data and image data to conduct a comprehensive analysis of temperature changes and generate comprehensive data for analysis. In this way, the comprehensive temperature change data at multiple locations in the oral cavity can help the AI ​​model analyze the health status of various surfaces in the oral cavity.

[0151] The data collection and power input and management process is as follows: the thermistor 331 probe collects the oral temperature in real time, and the thermistor 331 is connected in series with an independently installed voltage-dividing resistor 332 to form a voltage-dividing circuit, which converts the resistance change of the thermistor 331 into a voltage change. The voltage signal pin at the connection between the thermistor 331 and the independent voltage-dividing resistor 332 is directly connected to the ADC pin (GPIO35, ADC1_CH7) of the ESP through a flexible cable (FPC). The collected data is processed preliminarily by the chip module and a timestamp is added to ensure the integrity and traceability of the data. The 3.3V power line of the power module is introduced from the power module through a wire to connect the independent voltage-dividing resistor 332, and the independent voltage-dividing resistor 332 is connected in series with the thermistor 331. The GND is introduced from the power module to connect the thermistor 331, and the GND is then connected to the ground connection port of the power module to form a voltage-dividing circuit.

[0152] Odor data collection submodule 340

[0153] The odor data collection submodule 340 includes a gas collection terminal 341 (the fourth data collection terminal), a flexible air guide tube 342, a waterproof breathable membrane 343 and an odor sensor 344. The gas collection terminal 341 is arranged in an open shape at the toothbrush end 110, located on the side of the connection part 111 facing the handheld end 120, and on the side facing away from the connection part 111. The flexible air guide tube 342 is made of a medical PVC tube, one end of the flexible air guide tube 342 is connected to the gas collection terminal 341, and the other end is connected to the odor sensor 344. The waterproof breathable membrane 343 is a Gore-Tex or ePTFE membrane (whether detailed material is required), which is installed at the gas collection terminal 341, and allows the gas to pass through the collection terminal of the device body and flow to the odor sensor 344 under the guidance of the flexible air guide tube 342, while preventing the liquid from passing through the gas collection terminal 341 and entering the flexible air guide tube 342. The gas can flow to the odor sensor 344 through the flexible air guide tube 342, so that the odor sensor 344 can collect the gas and volatile organic compounds (VOCs) data in the oral cavity. The gas inlet of the odor sensor 344 is physically connected to the flexible air guide tube 342, and the other end is connected to the I2C interface of the chip module. The power is connected from the power pin of the second printed circuit board 360 to the VCC pin of the odor sensor 344, and the GND pin is connected to the GND pin of the odor sensor 344.

[0154] During the toothbrushing process, the odor collection submodule monitors the odor data in the oral cavity in real time. After the data is collected, the chip module in the toothbrush 10 adds a timestamp and performs other processing before sending it to the cloud. The odor data collected in the oral cavity can provide comprehensive analysis data for the AI ​​model professionally trained in the cloud, and combine with other data collected in the oral cavity at the same time to conduct a comprehensive analysis of odor changes. The odor change data generated in the cloud can help the AI ​​model analyze the oral health status. (AI can filter out unnecessary odor components of toothpaste and water through training)

[0155] Biological data collection submodule 350

[0156] The biological data acquisition submodule 350 includes a selective membrane 351, a reaction chamber 352 (the fifth data acquisition terminal), a microfluidic control chip 353, a one-way valve 354 and a biosensor 355. Among them, the reaction chamber 352 is arranged at the toothbrush end 110, and is located on the side of the connecting portion 111 facing the handheld end 120. The reaction chamber 352 is provided with an inlet and an outlet on the outer peripheral surface of the toothbrush end 110 for accommodating oral fluid samples. The biosensor 355 contacts the liquid sample in the reaction chamber 352 through a platinum electrode wire to ensure a stable reaction environment. Biocompatible materials are used to ensure harmlessness to the human body. The inlet and outlet of the reaction chamber 352 are provided with guide grooves and a waterproof structure to ensure that the liquid does not flow into the toothbrush 10 to avoid damage to other components.

[0157] The selective membrane 351 is set on the inlet, and the material is a highly selective material, biocompatible, high-throughput design with self-cleaning function. It can filter larger molecules or particles such as toothpaste and water, and only allow biomarkers in saliva to pass through. The reaction chamber 352 is connected to the biosensor 355 through a platinum electrode wire, and the liquid sample flows into the reaction chamber 352 and is filtered through the selective membrane 351.

[0158] The microfluidic chip is installed in the reaction chamber 352 and is made of biocompatible microfluidic chip materials. The microfluidic chip does not require additional power input and uses capillary action and the flow characteristics of the liquid itself to control the flow of the sample.

[0159] The one-way valve 354 is installed at the outlet guide groove of the reaction chamber 352. The size of the outlet guide groove must match the size of the one-way valve 354 and be sealed at the edge to prevent the repeated action of brushing teeth from causing the mixed liquid flowing out of the mouth to flow into the reaction chamber 352 through the outlet guide groove.

[0160] The biosensor 355 is embedded in the handheld end 120 of the toothbrush 10 and is miniaturized. The biosensor 355 uses an electrochemical sensor with a fast response time, and can usually detect a wide range of biological indicators within a few seconds. The biosensor 355 is connected to the reaction chamber 352 through a platinum electrode wire and extends into the reaction chamber 352. The biosensor 355 is connected to the ESP through the GPIO33 (ADC1_CH5) of the ADC interface, and obtains power through the standard I2C interface of the second printed circuit board 360. The biosensor 355 detects biomarkers (such as bacteria, enzymes, and pH values) in saliva in real time during brushing, and transmits the biological information to the chip module.

[0161] During the brushing process, the biological data acquisition module 300 monitors the biomarkers (such as bacteria, enzymes) and pH value in the saliva in the oral cavity in real time. After data collection, the data is sent to the cloud through the chip module in the toothbrush 10. The biological data collected in the oral cavity can provide comprehensive analysis data for the cloud AI model and further eliminate the interference of mixed liquids through cloud big data technology and AI models to achieve data accuracy, and combine with other data collected in the oral cavity at the same time to conduct a comprehensive analysis of oral health. Changes in biological data generated in the cloud can help the AI ​​model analyze oral health status.

[0162] The data collection and power input and management process is that during the brushing process, the stimulation of toothpaste and toothbrush 10 increases the oral secretion of saliva, with an average secretion of about 0.5 to 1.5 ml per minute. The mixed liquid in the mouth (saliva, toothpaste foam and water) passes through the guide groove set at the brushing end 110, and passes through the selective membrane 351 at the entrance of the reaction chamber 352. The selective membrane 351 filters out larger molecules or particles such as toothpaste and water, and only allows biomarkers in the saliva to pass through. The filtered saliva sample enters the reaction chamber 352, and the flow of the liquid sample in the reaction chamber 352 is guided and controlled by the microchannel in the microfluidic chip to ensure that the saliva sample stays at the sensor for enough time for detection. In order to ensure the continuous renewal and effective detection of the liquid sample in the reaction chamber 352, the reaction chamber 352 is designed with an outlet. After detection, the liquid sample is discharged from the reaction chamber 352 through the outlet guide groove, and at the same time, the new mixed liquid continuously flows into the reaction chamber 352 through the guide groove, forming a continuous liquid flow cycle. The platinum electrode wire is led out from the sensing electrode of the biosensor 355 at the handheld end 120 of the toothbrush 10, extends into the reaction chamber 352, and directly contacts the filtered saliva sample to detect biomarkers. The analog signal pin of the biosensor 355 is directly connected to the ADC pin (GPIO 33, ADC1_CH5) of the ESP. And the chip module adds a timestamp to the collected data.

[0163] The above content has described in detail the composition, structure and function of the data acquisition module 300. Next, other modules of the toothbrush 10 will be described in detail.

[0164] The chip module includes a third printed circuit board 410, a microcontroller chip 420 (ESP) and a display screen 430. The microcontroller chip 420 is integrated with various interfaces, connected to the third printed circuit board 410 through a standard connector, responsible for core processing and communication, and connected to various external sensor modules through pin headers. The GPIO interface is designed as follows: GPIO 19 is connected to the Hall sensor 317, GPIO 21 (SDA) is connected to the I2C device (multi-spectral optical sensor 316), GPIO 22 (SCL) is connected to the I2C device (multi-spectral optical sensor 316), GPIO 25 (SDA) is connected to the I2C device (odor sensor 344), GPIO 26 (SCL) is connected to the I2C device (odor sensor 344), GPIO 32 (ADC1_CH4) is connected to the pressure sensor, GPIO 33 (ADC1_CH5) is connected to the biosensor 355, GPIO 34 (ADC1_CH6) is connected to the angle sensor 318, and GPIO 35 (ADC1_CH7) is connected to the temperature acquisition module. The SPI interface is designed as follows: GPIO 18 is connected to the fingerprint recognition module, including MOSI, MISO, SCK and CS pins, and the display screen 430 is connected to the microcontroller chip 420 through the SPI interface. The display screen 430 is connected to the ESP via an SPI interface to ensure that necessary information can be displayed even in low power consumption mode. The display screen 430 obtains power through PCB3 to display power, data collection status, data transmission status, and signal status.

[0165] The chip module receives data from each sensor and classifies it according to the unique identifier (UID) of the sensor. Data encryption uses the AES-256 encryption standard to ensure data security during transmission. Timestamp addition adds timestamps to each data packet in real time to ensure data timing consistency. Data transmission transmits data to the cloud through the WiFi / Bluetooth submodule of the microcontroller chip 420. It is also responsible for power management, supports lightweight sleep mode and deep sleep mode, and automatically enters low-power standby state according to actual usage scenarios and needs. The screen displays the power of the built-in power module, whether the data acquisition module 300 is working, and the connection of the transmission signal.

[0166] The data processing flow of the chip module is as follows: data reception, each sensor data is transmitted to the microcontroller chip 420 through the GPIO, I2C, and ADC interfaces, and data reception simultaneously classifies the data and assigns the UID. The microcontroller chip 420 adds a timestamp to the received data to ensure the timing consistency of the data, and performs encryption processing (AES-256) to prevent remote intrusion and access to private data. The data is temporarily stored in the 4MB flash memory built into the microcontroller chip 420 until it is transmitted to the cloud. The encrypted data is transmitted to the cloud through the WiFi / Bluetooth submodule of the microcontroller chip 420.

[0167] The power module includes a fourth printed circuit board 510, a lithium battery 520, a charging management chip 530, a voltage regulator 540 and a fingerprint switch 550. Among them, the lithium battery 520 is a small lithium battery 520 with a capacity of 300mAh, which is integrated inside the power module and connected to other components through the fourth printed circuit board 510. The charging management chip 530 manages the charging of the lithium battery 520, which is integrated on the fourth printed circuit board 510 and connected to the Type-C interface for charging. The voltage regulator 540 is a low-dropout voltage regulator 540 (LDO) with an input voltage of 5V and an output voltage of 3.3V. The input 5V voltage is stably stepped down to 3.3V and provided to each module, which is integrated on the fourth printed circuit board 510. After the fingerprint switch 550 confirms the user's identity through fingerprint recognition, it activates the power supply of the power module, connects to ESP3 through the SPI interface, and the power input is connected to the output terminal and ground terminal (GND) of the fourth printed circuit board 510.

[0168] The functional flow of the power module is fingerprint recognition and power-on. When the user touches the fingerprint recognition panel of the fingerprint switch 550, the module wakes up and performs identity authentication. After the identity authentication is passed, the fingerprint switch 550 sends a signal to the microcontroller chip 420 through the SPI interface. After receiving the signal, the microcontroller chip 420 controls the switch of the power module, turns on the main power supply, and activates the entire system.

[0169] The above content describes in detail the specific structure of the toothbrush 10 in a specific embodiment. The present application also provides a control method 30 applied to the toothbrush 10. The specific steps of the control method 40 in the present application are described in detail below in conjunction with the accompanying drawings.

[0170] Figure 7 40 is a flow chart of the control method 40 in this application. Figure 7 As shown, the specific steps of the control method 40 in the present application include:

[0171] Step S901, power on.

[0172] In step S901, the user presses the fingerprint switch 550 with his finger, and the fingerprint switch 550 confirms the user's identity through fingerprint recognition and activates the power supply of the power module.

[0173] Step S902: Collect data.

[0174] In step S902, when the user is brushing his teeth, the data collection module 300 collects data in the oral cavity, obtains oral information, and stores the oral information in the data storage module.

[0175] The image data acquisition submodule 310 uses a specific wavelength LED light source 312 in the selected wavelength range of 660nm-750nm to perform high-resolution scanning of shallow tissues such as teeth, gums, tongue, and oral cavity inner wall through reflected light intensity measurement and spectral analysis during the brushing process. The data collected by the optical sensor 316 module and the data collected by the Hall sensor 317 and the angle sensor 318 are sent to the chip module built into the toothbrush 10, and the chip module adds a time stamp.

[0176] During the brushing process, the pressure sensor monitors the pressure on the teeth in real time and converts it into an electrical signal. The pressure sensor captures the pressure data of different parts by detecting the pressure changes. These data will be transmitted to the chip module built into the toothbrush 10. In the chip module, the pressure data will be timestamped and spatially marked in combination with the position information collected by the image data.

[0177] The temperature data acquisition module 300 monitors the temperature data of each area or area point in the oral cavity in real time during the toothbrushing process. After data acquisition, the data will be processed by the chip module in the toothbrush 10, including adding timestamps and spatial tags. The spatial tag is based on the location information of the image data acquisition to ensure that the temperature data corresponds to the image data of the specific location in the oral cavity.

[0178] The odor data collection module 300 monitors the odor data in the oral cavity in real time during the toothbrushing process. After the data is collected, a time stamp is added and other processing is performed through the chip module in the toothbrush 10.

[0179] During the brushing process, the biological data collection module 300 monitors the biomarkers (such as bacteria, enzymes) and pH value in the oral saliva in real time. After the data is collected, it is sent to the chip module in the toothbrush 10, and the chip module adds a time stamp to the data.

[0180] Step S903: upload data.

[0181] In step S903, after the chip module processes the data collected by the data collection module 300, the data is transmitted to the cloud via the WiFi / Bluetooth submodule in the chip module.

[0182] Step S904: Analyze data.

[0183] In step S904, after the data is uploaded to the cloud, a professionally trained AI model provides comprehensive analysis data in the cloud through big data technology, combining all types of data collected simultaneously in the oral cavity. The professionally trained AI model can produce detailed analysis results, predict and warn the occurrence and development of oral diseases in advance.

[0184] Step S905: Issue a prompt message.

[0185] In step S905, after obtaining the analysis structure of the AI ​​model, the cloud will send advance predictions and warnings of the occurrence and development of oral diseases to the user's mobile phone, tablet computer, computer and other human-computer interaction devices 30. The user can view the prompt information through the human-computer interaction device 30 to determine the health status of the oral cavity.

[0186] Below, in a specific embodiment, the oral health management system in the present application is described in detail.

[0187] The technical architecture design of the oral health management system in this application is divided into three core layers: data collection layer, data processing and analysis layer, and user interaction and integration layer. Among them, the data collection layer is implemented by the above-mentioned toothbrush 10, the data processing and analysis layer is implemented by the server 20 in the cloud, and the user interaction and integration layer is implemented by the human-computer interaction device 30. These layers together constitute a complete closed-loop system from smart device data collection to cloud processing and then to user feedback.

[0188] The data collection layer is mainly composed of smart devices such as the above-mentioned toothbrush 10 with multi-dimensional data collection, which are equipped with a variety of sensors, including image, pressure, smell, temperature and biosensors. The device transmits the collected oral health data to the cloud in real time through wireless communication protocols (such as Wi-Fi or Bluetooth). In order to ensure real-time, especially for the collection and preliminary filtering of odor data, these data will enter the next layer for processing immediately after uploading.

[0189] The data processing and analysis layer is located in the cloud and is divided into two subsystems: the big data processing system and the large model analysis system. The big data processing system is responsible for preliminary data cleaning and preprocessing, especially the rapid filtering of odor data. The system uses big data technology frameworks (such as Hadoop and Spark) to quickly identify and exclude toothpaste ingredients from odor data, and standardize and store all collected data. This process ensures the quality and consistency of the data while providing high-quality input for further analysis of the large model. The large model analysis system performs more complex in-depth analysis, especially the fusion of multimodal data and the identification of health patterns. Based on deep learning algorithms (such as CNN and Transformer), the system conducts comprehensive analysis of data from different sources to generate detailed health reports and predictions. This part can be processed with a delay (such as within 12 hours) after data preprocessing to ensure the accuracy and depth of the analysis.

[0190] The user interaction and integration layer involves the interaction between users and the system and data integration with medical institutions. Users receive real-time health feedback through mobile applications, especially the preliminary analysis results of odor data. At the same time, the system also supports delayed in-depth analysis reports to provide users with more comprehensive health advice after a few hours. The platform provides standardized API interfaces (such as FHIR) to achieve data sharing and integration with medical institutions, supporting precision medicine and further health management.

[0191] The oral health management system adopts a modular design, including a data acquisition module 300 (corresponding to the data acquisition layer), a data processing and analysis module (corresponding to the data processing and analysis layer), a user interaction module (corresponding to the user interaction and integration layer) and a data security and privacy module.

[0192] The data acquisition module 300 is provided in a toothbrush 10 with a multi-dimensional data acquisition function. A variety of sensors are integrated to collect and transmit the user's oral health data in real time. In particular, the odor sensor focuses on quickly collecting data while brushing teeth so as to immediately enter the data processing layer for preliminary analysis.

[0193] The toothbrush 10 is the core hardware component of this project. Its design and technical implementation are to efficiently collect a variety of health data in the oral cavity during daily brushing. The toothbrush 10 integrates a variety of sensor modules, such as Figure 5 As shown, the data acquisition module 300 in the toothbrush 10 includes an image data acquisition submodule 310, a pressure data acquisition submodule 320, a temperature data acquisition submodule 330, an odor data acquisition submodule 340 and a biological data acquisition submodule 350. They are respectively used to collect images, pressure, temperature, odor and biological data in real time, ensuring that comprehensive and continuous health data is obtained during the user's brushing behavior.

[0194] The temperature data acquisition submodule 330 is used to monitor the temperature data of various areas in the oral cavity. These data, combined with the image data, are helpful for analyzing the health of the oral cavity. Specifically, the temperature data acquisition submodule 330 collects temperature data in real time through a thermistor probe embedded in the main body of the toothbrush head 10 base, and processes and uploads it through the chip module.

[0195] The odor data collection submodule 340 is used to monitor the odor data in the oral cavity, especially volatile organic compounds (VOCs). These data have the highest processing priority after collection, and need to be analyzed and fed back to the user end in a short time to help users understand the source and health status of oral odor in a timely manner. Specifically, the odor data enters the odor sensor in the toothbrush 10 through the flexible airway. The collected data is immediately processed by the chip module (such as adding a timestamp) and uploaded to the cloud. The analysis system in the cloud will give priority to processing these data, quickly generate analysis results, and feed back the results to the user end in the shortest time so that the user can take timely measures.

[0196] The biological data collection submodule 350 collects biological data in the oral cavity, such as bacteria, enzymes, and pH values ​​in saliva. These data, combined with other collected data, can help the cloud AI model perform a more comprehensive health analysis. Specifically, when brushing your teeth, the mixed liquid sample is filtered through a selective membrane to remove larger molecules or particles to ensure that only target biomarkers (such as bacteria, enzymes, pH values, etc.) can pass. Next, the filtered sample enters the microfluidic chip and is guided to the biosensor through a finely controlled fluid channel. The biosensor detects these biomarkers and generates corresponding electrical signals. These data are then processed by the chip module and uploaded to the cloud for further health analysis.

[0197] The data processing and analysis module (corresponding to the data processing and analysis layer) includes a big data processing submodule and a large model analysis submodule. The big data processing submodule first cleans, denoises and standardizes all collected data, especially for rapid filtering and preliminary analysis of odor data to ensure the timeliness and accuracy of the data. The large model analysis submodule is responsible for in-depth health pattern recognition and generates personalized health reports based on multimodal data. This part of the analysis can be delayed to provide more accurate health advice.

[0198] After data collection is completed, the system first enters the data preprocessing and big data processing stage. The main task of this stage is to ensure that the collected data is cleaned, standardized and preliminarily processed to provide high-quality data input for subsequent large model analysis. This process includes multiple key steps, from data cleaning to preprocessing, storage and management, to ensure the quality and consistency of the data.

[0199] Next, the specific contents of data processing in the big data processing submodule are introduced in detail.

[0200] 1. Data cleaning and standardization

[0201] High-precision processing of image data

[0202] Technical implementation: Image data is collected multiple times and at multiple angles, and processed using edge detection, spectral analysis, and noise suppression technology. The system uses image stitching and 3D reconstruction technology to integrate these data into a high-resolution intraoral digital image model to ensure the accuracy and stability of the model, providing a high-quality visual basis for subsequent analysis.

[0203] Processing of pressure data

[0204] Technical implementation: After the pressure data is collected, the system performs preliminary processing through time series and spatial analysis techniques. These processes mainly focus on data cleaning, outlier processing and noise filtering to ensure the integrity and temporal consistency of the pressure data. The processed data will be used to identify pressure change patterns associated with loose teeth and provide accurate data input for further analysis.

[0205] Temperature data processing

[0206] Technical implementation: Temperature data is collected in real time through sensors such as thermistors. The system performs preliminary processing on this data, including noise filtering and data smoothing, to eliminate interference from changes in external ambient temperature. The processed temperature data will be combined with image data to provide more accurate oral area temperature information, which helps identify health problems such as inflammation or infection.

[0207] Interference filtering of odor data

[0208] Technical implementation: In the odor data preprocessing stage, the system matches and filters through the database of known toothpaste ingredients and other common interferences (continuous collection). This process uses pattern recognition technology to eliminate interference factors such as toothpaste and mouthwash to ensure the purity of the odor data and provide accurate input data for the subsequent large model analysis stage.

[0209] Noise filtering of biological data

[0210] Technical implementation: The processing of biological data pays special attention to the elimination of interfering factors. The collected saliva samples are first filtered through a selective membrane to remove larger molecules and non-target components. Since the reaction chamber cannot completely ensure the purity of the collected specimens, the system pre-collects and analyzes the biological components of all toothpastes on the market (continuously collected) and stores the characteristics of these components in the database. During the data cleaning process, the system uses this pre-stored toothpaste ingredient information and, through pattern recognition and matching technology, excludes or marks toothpaste-related biological components as potential interferents, ensuring that the biological data ultimately used for analysis is highly accurate and consistent.

[0211] 2. Data storage and preliminary processing

[0212] Data Fusion

[0213] Technical implementation: The system integrates image, pressure, temperature, odor, biological and other data into a unified framework through multimodal data fusion technology. Data aggregation and pattern recognition methods are used in this process to ensure that information between different data sources can be effectively integrated. This fusion step provides highly relevant and consistent data input for subsequent large model analysis.

[0214] Data storage and management

[0215] Technical implementation: The cleaned and standardized data is stored in a distributed database system, such as Hadoop HDFS or similar distributed storage architecture. Distributed storage improves the high availability and redundancy of data and provides a reliable foundation for subsequent large-scale analysis.

[0216] 3. Prioritization of odor data

[0217] Real-time data transmission

[0218] Technical implementation: Although the system mainly performs preprocessing in the big data stage, due to the high priority of odor data, the system will mark it as urgent data and transfer it to the large model analysis stage first. Through data marking and priority queue management, it ensures that the odor data can enter the deep analysis process as soon as possible, thereby achieving rapid feedback.

[0219] 4. Data cleaning

[0220] Removing noise and outliers

[0221] Noise Removal: Identify and remove noise in the data, such as invalid data caused by sensor failure or random outliers.

[0222] Outlier handling: Identify outliers and decide whether to remove, correct, or keep them. Usually identified through statistical methods (such as Z-score, IQR) or model testing.

[0223] Missing data handling

[0224] Deleting missing values: Data columns or rows with extremely high missing values ​​may be deleted directly to reduce the impact on the analysis.

[0225] Interpolation of missing values: Use statistical methods such as mean, median, mode or more complex interpolation techniques (such as KNN interpolation, regression interpolation) to fill in missing data and maintain data integrity.

[0226] Data consistency check

[0227] Format unification: Ensure that all data formats are unified, such as date format, numerical unit, etc., and handle format inconsistencies from different data sources.

[0228] Duplicate value processing: Find and delete duplicate records to avoid the impact of data redundancy on analysis.

[0229] 5. Data preprocessing

[0230] Data standardization and normalization

[0231] Standardization: Convert the data to a distribution with zero mean and unit variance, which is suitable for distance-based machine learning algorithms such as SVM and KNN.

[0232] Normalization: Scaling the data to a specified range (usually between 0 and 1), which is especially important for models such as neural networks that are sensitive to the data range.

[0233] Feature extraction and selection

[0234] (Feature extraction: extracting useful features from raw data, such as breaking down timestamps into hours, minutes, etc., or extracting edge features from image data.

[0235] Feature selection: Select the most important features through statistical methods or machine learning techniques to reduce dimensions, improve model performance and reduce computational complexity.

[0236] Data Augmentation

[0237] Synthesizing new data: When the amount of data is insufficient, new data points are generated using existing data, such as data flipping, rotation, noise addition, etc. This is particularly common in image processing and deep learning.

[0238] Data conversion

[0239] Categorical variable processing: Convert categorical variables into numerical representations, such as using One-Hot encoding or Label encoding, so that they can be used by machine learning models.

[0240] Data binning: Divide continuous variables into discrete intervals to help the model better handle nonlinear relationships.

[0241] 6. Data integration and segmentation

[0242] Multimodal data fusion

[0243] Technical implementation: Data from different sensors are synchronized in time and aligned in space to ensure consistency of various data at the same time point and in the same spatial range. The fusion of multi-source data creates a unified data set, providing a solid foundation for subsequent analysis and modeling.

[0244] Partitioning of training, validation, and test sets

[0245] Technical implementation: In the process of machine learning, data is usually divided into training sets, validation sets, and test sets to evaluate the performance of the model and prevent overfitting.

[0246] Next, the specific contents of large model analysis performed by the large model analysis submodule are introduced in detail.

[0247] After data preprocessing and big data processing are completed, the system enters the large model analysis stage. In this stage, through deep learning and complex model reasoning, multimodal data is fully integrated and deeply analyzed to generate high-precision health assessments, personalized recommendations, and health warnings.

[0248] 1. Training and reasoning of large models

[0249] Model Training

[0250] Technical implementation:

[0251] (1) Construction and annotation of data sets:

[0252] Before training a large model, you first need to build a multimodal dataset, which includes annotated oral images, pressure data, temperature data, odor data, biomarker data, etc. These datasets are completed by manual or automatic annotation tools to ensure the diversity and high quality of training data. This is the basis for model training and determines the performance of the model in practical applications.

[0253] (2) Multimodal data fusion:

[0254] Large models need to process and fuse multiple data types from different sensors. Using graph convolutional networks (GCNs) and self-attention mechanisms, the model can effectively learn the complex relationships between different data types. This can strike a balance between the accuracy and breadth of analysis, ensuring comprehensive detection of various health conditions.

[0255] (3) Model training process:

[0256] The model training process includes the following steps:

[0257] Initialize model parameters: Initialize the weights and structure of the model according to the characteristics of multimodal data.

[0258] Forward propagation and loss calculation: Through forward propagation, the gap between the model output and the true label (i.e., the loss function) is calculated.

[0259] Backpropagation and parameter update: The gradient of the loss function is calculated using the backpropagation algorithm and the model parameters are updated through an optimization algorithm such as Adam or SGD.

[0260] Multiple rounds of iterative training: Repeat the above steps until the model's loss function becomes stable, indicating that the model has converged.

[0261] Transfer learning and fine-tuning: To improve the generalization ability of the model, a model pre-trained on a large-scale general dataset may be used and fine-tuned on a specific health dataset.

[0262] Model Inference

[0263] Technical implementation:

[0264] (1) Real-time reasoning and batch processing:

[0265] When receiving real-time data, the model generates immediate health assessment results through fast forward propagation. For batch historical data, the system provides long-term health trend analysis and assessment through comprehensive analysis of time series data (such as time series alignment using the dynamic time warping DTW algorithm).

[0266] (2) Optimizing inference speed:

[0267] In order to achieve efficient reasoning in the cloud, the model will be optimized, such as pruning, quantization, etc. These optimization techniques reduce the complexity of the model, thereby reducing the demand for computing resources and the delay of reasoning.

[0268] (3) Output health assessment and recommendations:

[0269] The output of the model includes comprehensive health assessment, personalized health recommendations, health warnings, etc. These results are communicated to users through user-side applications, allowing them to understand their health status in a timely manner and take appropriate measures.

[0270] 2. Health status analysis

[0271] Oral health status

[0272] Analysis goal: Through the fusion of multimodal data (such as joint analysis of image data and pressure data), the system can identify health problems of soft tissues such as teeth, gums, and the inner wall of the mouth. The model can not only detect current oral health problems (such as caries, periodontal disease, oral ulcers, etc.), but also predict potential disease development trends. The results of this analysis will be presented in the form of a health report, providing early warning information about possible disease development paths.

[0273] Physical health

[0274] Analysis goal: By analyzing changes and anomalies in multimodal data in the mouth, the system can infer the user's overall health status. Specifically, through the combination of odor and biomarker data, the model can detect potential systemic diseases such as diabetes, gastrointestinal problems, or immune system abnormalities. Based on these analysis results, the system will generate early warnings about potential systemic health problems and prompt the user through the user interface that further examination may be needed.

[0275] The accuracy and breadth of data fusion

[0276] Technical implementation: In order to ensure the accuracy and breadth of the analysis results, the system deeply integrates all data types during the analysis process. Through the combination of self-attention mechanism and multimodal neural network, the system can comprehensively consider the impact of various types of data from multiple dimensions and improve the reliability of the analysis results. Through this data fusion, the system can provide more accurate health status assessment and early warning.

[0277] 3. Personalized health advice

[0278] Health management advice

[0279] Analysis goal: Based on the comprehensive analysis of oral and physical health conditions by the big model, the system generates personalized health management recommendations. These recommendations not only involve oral health maintenance, but also cover improvements in lifestyle habits, eating habits, etc. Depending on the specific health problem, the system may recommend suitable over-the-counter medicines or other oral care products to help users improve or maintain overall health.

[0280] Health warning and medical advice

[0281] Analysis goal: When the system detects a potential serious health problem, it will generate a health warning and recommend that the user seek medical attention as soon as possible. Health warnings are based on monitoring the user's long-term health trends, paying special attention to abnormal changes in the data, and combining current health data to provide immediate warning information. Depending on the severity of the health risk, the system will recommend the department the user needs to visit and the further examinations or treatment measures that may be needed.

[0282] Delayed instruction to improve brushing behavior

[0283] Analysis goal: The system provides delayed feedback based on the user's brushing data, especially pressure and image data, through comprehensive evaluation after multiple analyses. Although this function is a feature of many existing products, the brushing habit improvement suggestions generated by the system through delayed analysis are more personalized. By gradually adjusting the user's brushing behavior, oral health can be effectively improved. These improvement suggestions will be sent to users through user interaction programs to help them make appropriate adjustments in their daily lives.

[0284] Next, other technical solutions of the cloud server 20 are described (except big data and big model technologies).

[0285] In order to realize the comprehensive functions of the oral health management system and ensure the efficiency and security of the system, the project will deploy the following key technical components in the cloud. These technologies cover distributed computing, containerization, real-time processing, security and other aspects.

[0286] 1. Distributed computing and storage:

[0287] Distributed computing architecture:

[0288] Use distributed computing frameworks such as Apache Hadoop or Apache Spark to process and analyze large-scale data sets. These frameworks can be deployed on local cloud services in China (such as Alibaba Cloud, Tencent Cloud, Huawei Cloud, etc.) to ensure processing efficiency and system scalability.

[0289] Application scenarios: Suitable for scenarios with high-concurrency data processing and large-scale computing tasks, improving cloud computing capabilities.

[0290] Distributed storage:

[0291] Use local distributed storage systems such as Alibaba Cloud OSS (object storage service) or Tencent Cloud COS (object storage service) to store diverse health data. Distributed storage provides high availability, disaster recovery capabilities, and efficient data access.

[0292] Application scenarios: Used to store users' health data, model training data sets, and analysis results to ensure data security and efficient access.

[0293] 2. Containerization and Microservice Architecture

[0294] Containerization technology:

[0295] Use Docker combined with Kubernetes for containerized deployment. Use the Kubernetes engine provided by local cloud services (such as Alibaba Cloud's ACK and Tencent Cloud's TKE) to achieve cross-platform operation and rapid deployment of applications.

[0296] Application scenarios: In development and production environments, containerization ensures application consistency on different hardware and operating systems and simplifies application expansion and management.

[0297] Microservices Architecture:

[0298] Adopt microservice architecture to modularize system functions. Use API gateway for communication and coordination, and use local API gateway services (such as Alibaba Cloud API Gateway and Tencent Cloud API Gateway) to achieve efficient interaction between services.

[0299] Application scenarios: Enhance the flexibility, scalability and fault tolerance of the system, suitable for complex system architecture.

[0300] 3. Real-time data processing and streaming computing

[0301] Real-time data processing:

[0302] Use stream processing frameworks such as Apache Kafka or Alibaba Cloud DataHub to process real-time data streams. Local cloud services in China (such as Alibaba Cloud's real-time computing Flink) can support the collection and processing of large-scale real-time data.

[0303] Application scenarios: After the data collection toothbrush 10 uploads the data to the cloud, it is processed and fed back immediately, which is suitable for application scenarios that require real-time analysis and response.

[0304] 4. Security and disaster recovery backup

[0305] High availability with automatic failover:

[0306] Through multi-availability zone deployment architecture such as Alibaba Cloud or cross-availability zone architecture of Tencent Cloud, high availability and automatic failover of the system in different geographical locations are ensured. When an instance in a certain area has a problem, the system will automatically switch to an instance in another area to ensure service continuity.

[0307] Application scenarios: Applicable to critical business applications to ensure system reliability and continuous availability.

[0308] Data backup and recovery:

[0309] Perform automated data backups regularly and store the backup data in an offsite data center, using services such as Alibaba Cloud Disaster Recovery or Tencent Cloud Backup and Recovery. Establish a disaster recovery plan (DRP) to ensure that data and services can be quickly restored in extreme situations.

[0310] Application scenario: Protect the integrity and security of user data, especially in the event of a natural disaster or system crash.

[0311] The user interaction module provides real-time feedback of the quickly processed odor data results to users through the mobile application, and provides a more comprehensive health analysis report a few hours later. The application is designed to be simple and intuitive, and supports user-defined health reminders and alarm settings. The user interaction module is also equipped with a data sharing interface, providing a standardized API interface with medical institutions, and supporting two-way communication and synchronization of data. Private hospitals can achieve deep integration, while public hospitals mainly rely on one-way data sharing and manual uploading.

[0312] The data security and privacy module is used for data encryption and privacy protection. The Advanced Encryption Standard (AES-256) is used throughout the process to protect data, and it strictly follows the "Cybersecurity Law of the People's Republic of China" and the "Personal Information Protection Law" to ensure user privacy.

[0313] In the user interface and feedback mechanism part of the project, the system mainly provides users with comprehensive oral health monitoring, hidden danger warning, lifestyle improvement suggestions, and medical treatment suggestions through intuitive and easy-to-use interface design combined with multiple feedback mechanisms. This section will describe the design and technical implementation of these core functions in detail.

[0314] 1. User interface design

[0315] Interface design principles

[0316] Technical implementation:

[0317] User-friendliness: The user interface design follows the principle of simplicity and intuition, ensuring that users can easily access and operate the various functions of the system. The interface adopts a flat design, uses clear icons and a reasonable layout, allowing users to quickly understand and use the system.

[0318] Responsive design: The interface design supports multiple devices and adopts a responsive layout, which can automatically adjust the display effect according to the screen size of different devices, ensuring a consistent and good user experience on smartphones, tablets and computers.

[0319] Key interface features

[0320] Technical implementation:

[0321] Oral Health Dashboard: The core part of the user interface is the Oral Health Dashboard, which displays the user's oral health indicators in real time, including the condition of soft tissues such as teeth, gums, and the inner wall of the mouth, as well as the impact of diet and lifestyle habits on oral health. Through charts and graphical methods, users can understand their overall oral health status at a glance.

[0322] Display of health warnings and medical advice: The interface provides a special area to display health warnings and medical advice generated by the system, helping users to detect potential oral or systemic health problems early, and providing corresponding medical advice, including recommendations for appropriate departments and possible examinations.

[0323] Interaction Design

[0324] Technical implementation:

[0325] Voice and gesture interaction: The system supports voice and gesture operations, and users can navigate the interface through simple voice commands or gestures. Voice recognition technology supports users to check health status, get health advice or set health reminders, further improving the convenience of user experience.

[0326] 2. Feedback Mechanism

[0327] Delayed feedback

[0328] Technical implementation:

[0329] Health trend analysis and push notifications: The system analyzes the user's health trends through the loss and missing information found during the data collection process, and regularly generates health reports and pushes them to the user. The health report includes the user's oral health change trends, potential health risks and their possible impact on overall health. The push content is intended to help users adjust their lifestyles or seek medical treatment in a timely manner.

[0330] Health monitoring and early warning

[0331] Technical implementation:

[0332] Hidden danger warning: The system conducts comprehensive analysis of the user's multimodal data, monitors oral health in real time, and provides hidden danger warnings when potential problems are detected. The system will provide detailed instructions and suggestions based on the severity of the warning, including the recommended department to visit and the preventive measures that need to be taken.

[0333] Lifestyle improvement suggestions: Based on the user's oral health data, the system will analyze the impact of the user's diet, lifestyle habits, etc. on oral health and provide improvement suggestions. For example, the system may recommend reducing the intake of certain types of food or increasing specific oral care habits to prevent potential oral health problems.

[0334] Product Recommendations

[0335] Technical implementation:

[0336] Oral care products and over-the-counter drug recommendations: The system intelligently recommends suitable oral care products and over-the-counter drugs based on the user's oral health status. These recommendations are based on the user's specific health needs, such as care products for gingivitis, or over-the-counter drugs for relieving oral ulcers. Recommendations are intuitively displayed through the user interface, with usage suggestions and purchase links.

[0337] Data analysis and health warning

[0338] Technical implementation:

[0339] Physical health warning: Through in-depth analysis of oral health data, the system can detect systemic health risks that some oral health problems may indicate (such as early signs of diabetes). When the system finds these risks, it will send health warnings through the user interface and provide specific action suggestions, such as suggesting that users undergo relevant systemic health examinations.

[0340] 3. User data management

[0341] View and manage health data

[0342] Technical implementation:

[0343] Health data visualization: The user interface provides a visualization function for health data, allowing users to view daily, weekly or monthly health changes. The system helps users understand the health trends behind the data through charts and graphics.

[0344] Data export and sharing: Users can export their health data or choose to share the data with doctors for further analysis. Data export supports PDF or CSV format to ensure data security and privacy protection.

[0345] User Privacy Settings

[0346] Technical implementation:

[0347] Privacy control: Users can customize privacy settings to control which data can be used or shared by the system. Users have the right to choose to share data anonymously for scientific research or limit the scope of data use to ensure that privacy is fully protected.

[0348] 4. Data Sharing Mechanism

[0349] Two-way data exchange model in private dental hospitals

[0350] Description of two-way data communication mode:

[0351] Real-time data sharing: A two-way data sharing channel is established between the platform and private dental hospitals, allowing both parties to exchange patients' oral health data in real time. Through the API interface, the patient's oral health monitoring data can be automatically synchronized to the hospital's electronic health record (EHR) system, helping doctors to have a more comprehensive understanding of the patient's health status.

[0352] Doctors’ feedback and suggestions: After receiving and analyzing patient data, doctors at private dental hospitals can push personalized treatment suggestions or care instructions to patients through the platform. These suggestions will be combined with the personalized health management function of the platform to further optimize the user’s oral care plan.

[0353] Data permissions and security: Patients can set their own data sharing permissions and decide which data can be accessed by the hospital. At the same time, data is encrypted during the sharing process to ensure privacy and security.

[0354] One-way data provision and user manual upload mechanism in public hospitals

[0355] One-way data provision mode description:

[0356] Data upload and sharing: For public hospitals, the platform mainly provides a one-way data upload function. Users can choose to manually upload oral health monitoring data to the EHR system of public hospitals. This method is mainly suitable for situations where public hospitals lack real-time data interaction with external platforms.

[0357] Post-diagnosis data update: After users receive diagnosis and treatment services from public hospitals, the doctor's diagnosis and treatment recommendations will not be automatically fed back to the platform. Users need to manually upload diagnosis and treatment information (doctor's orders, etc.) to the platform so that the platform can conduct further health management and data analysis. The platform will provide a simple upload interface so that users can easily add relevant data.

[0358] Data integration and display: Data uploaded to the platform will be automatically integrated into the user's health record for users to review at any time, and will be seamlessly integrated with the platform's health management functions.

[0359] 5. Data integration technology (use of standardized API):

[0360] API Interoperability and Integration

[0361] Introduction to FHIR Standard:

[0362] FHIR (Fast Healthcare Interoperability Resources) is an international standard for promoting interoperability of medical data between different systems. The platform adopts the FHIR standard to ensure smooth data integration with systems of various medical institutions (such as EHR systems). FHIR simplifies the exchange process of medical data by defining resources and data formats, enabling different systems to understand and process each other's data.

[0363] API design and implementation:

[0364] Standardized API design: Standardized APIs based on FHIR support common medical data exchange operations, such as querying, updating, and deleting patient data. These API interfaces can be seamlessly connected with the systems of private and public medical institutions to ensure accurate data transmission and integration.

[0365] Data format conversion: To ensure data interoperability, the platform implements a conversion mechanism from internal data formats to FHIR standard formats. Whether it is image data, health indicators or text reports, the platform will automatically convert them into structured data that complies with the FHIR standard so that they can be exchanged between different systems.

[0366] Scalability and compatibility: The platform’s API design is highly scalable and can be customized according to the needs of different medical institutions. At the same time, the platform is also compatible with other common medical data standards, such as HL7 and DICOM, further enhancing the flexibility and wide applicability of data integration.

[0367] Seamless data integration process

[0368] Integration process description:

[0369] Real-time synchronization and batch processing: The platform supports real-time data synchronization, ensuring that the patient's latest health data can be instantly transmitted to the medical institution's system. In addition, the platform also supports batch data processing, which is suitable for large-scale data import or data history backtracking needs.

[0370] Automated data connection: Through the automated connection of FHIR API, the platform can seamlessly connect with the hospital system to achieve automatic data transmission and processing. This not only reduces the need for manual intervention, but also improves the accuracy and efficiency of data transmission.

[0371] Data verification and confirmation: During the data integration process, the platform will perform multi-level data verification to ensure that the data is not tampered with or lost during the transmission process. After all data transmission is completed, the system will generate a confirmation log to record the details of the data exchange for future auditing and tracking.

[0372] Next, the new features and optimizations of the oral health management system platform are explained.

[0373] 1. Performance test plan:

[0374] Response time test: Test the system response time under multi-user concurrent use to ensure that the system can quickly respond to user requests under high load conditions. Use stress testing tools (such as JMeter) to simulate a large number of user accesses and measure the system response time under different loads.

[0375] Processing speed test: evaluates the speed of the system in processing large-scale data, including the time for data preprocessing, model inference, and result generation. Test different data volumes (such as 100GB and 500GB) and the time required for the system to process each data set.

[0376] Throughput test: Test the number of requests that the system can handle per unit time (such as the number of requests per second) and the amount of data processed per second. Evaluate whether the system can maintain stable performance at maximum throughput.

[0377] 2. System optimization

[0378] Data processing efficiency optimization:

[0379] Combining batch processing with real-time processing: Combining real-time processing with batch processing can optimize the data preprocessing speed. In the processing of high-priority data (such as odor data), a real-time processing mechanism is adopted, while historical data is batch processed, thereby improving the overall processing efficiency.

[0380] Data caching and pre-fetching: Introduce a data caching mechanism to load commonly used data and model results in advance in the system to reduce waiting time during real-time processing. Pre-fetch frequently accessed data to improve system response speed.

[0381] Model inference speed optimization:

[0382] Model pruning and quantization: Reduce redundant neurons and layers through model pruning, and reduce model complexity. Use model quantization technology to convert floating-point operations into fixed-point operations, significantly improve inference speed and reduce memory consumption.

[0383] Distributed reasoning architecture: During the reasoning process, a distributed computing architecture is used to distribute reasoning tasks to multiple servers 20 for parallel processing to improve the overall reasoning speed and enhance the scalability of the system.

[0384] User interaction optimization:

[0385] Responsive design: Ensure that the user interface displays consistently on a variety of devices (such as mobile phones, tablets, and computers), and provide a degraded experience when network conditions are poor to ensure that users can use the system smoothly.

[0386] Asynchronous request processing: When users are operating, asynchronous processing is used to reduce the sense of interface jamming. By optimizing the interaction between front-end requests and back-end responses, the user experience is made smoother.

[0387] Next, the data security and privacy protection of the oral health management system are explained.

[0388] In a data-driven system, data security and privacy protection are crucial links. In order to ensure the security and privacy of user data, the platform has implemented a series of technical measures and compliance programs in data encryption, privacy protection and security auditing.

[0389] 1. Data encryption

[0390] Data transmission encryption:

[0391] Technology application: During data transmission, the platform uses the Transport Layer Security Protocol (TLS) to encrypt all communications. This ensures that all data transmitted between the client and the server 20 is encrypted to prevent the data from being stolen or tampered with during transmission. The TLS protocol not only protects the confidentiality of the data, but also ensures the consistency of the data during transmission through data integrity verification.

[0392] Application scenarios: In particular, the transmission of user login information, health data upload, and model inference results are all encrypted through the TLS protocol. For the transmission of sensitive data, such as biomarker data and health warning information, the system uses the Advanced Encryption Standard (AES) for additional symmetric encryption to ensure high data security.

[0393] Data storage encryption:

[0394] Technology application: The platform uses the AES-256 standard to encrypt all data stored on the server 20. AES-256 is a symmetric encryption algorithm and is widely regarded as one of the most secure encryption algorithms currently available. All user data is encrypted before storage, and even if an unauthorized user obtains the storage medium, the content cannot be deciphered.

[0395] Key management: To ensure the security of encryption keys, the platform uses the Key Management Service (KMS) to generate, store and manage encryption keys. KMS ensures the security of the keys themselves and further improves the strength of data protection through automatic key rotation.

[0396] 2. Privacy protection

[0397] User data anonymization:

[0398] Technology application: During data collection and processing, the platform anonymizes user data. Anonymization technologies include de-identification (such as removing or encrypting identity information) and data disguise (such as hiding original data by adding noise or generating pseudo data). These measures effectively reduce the risk of data leakage or abuse.

[0399] Differential privacy: To further protect user privacy, the platform applies differential privacy technology to ensure that individual data is unidentifiable during statistical analysis and data sharing. Differential privacy protects user data from reverse identification by adding appropriate random noise while still ensuring the accuracy of data analysis.

[0400] Privacy compliance measures:

[0401] Legal compliance: All privacy protection measures of the platform strictly comply with the Cybersecurity Law of the People's Republic of China and the Personal Information Protection Law. This includes privacy protection measures during the collection, storage, processing and sharing of user data to ensure that data use complies with the requirements of national laws and regulations.

[0402] User informed consent: Before collecting and processing user data, the platform will clearly explain to users the purpose, scope and protection measures of data use through clear user agreements and privacy policies, and will only process their data after obtaining the user's informed consent. Users have the right to choose the scope of data sharing and can withdraw their consent at any time.

[0403] 3. Security Audit and Compliance

[0404] Regular safety audits:

[0405] Audit process: The platform implements regular security audits to ensure that the system's security policies and protection measures are effectively implemented. Security audits include comprehensive inspections of data access control, encryption mechanisms, log records, etc., to identify potential security vulnerabilities and repair them in a timely manner.

[0406] Third-party audits: To enhance the objectivity and authority of audits, the platform regularly invites third-party security companies to conduct independent audits to evaluate the overall security and data privacy protection measures of the platform. The audit reports will be provided to the platform management and used as a basis for improving security strategies.

[0407] Emergency response mechanism:

[0408] Rapid response: The platform has established a comprehensive emergency response mechanism to deal with emergencies such as data leaks or system attacks. An emergency response team is formed to quickly locate problems, contain risks, and develop repair plans after an incident occurs.

[0409] Regular drills: The platform conducts emergency response drills every quarter to simulate different types of security incidents (such as data leaks, DDoS attacks, etc.) to test the emergency response team's reaction speed and problem-solving capabilities. Through drills, the emergency response process and tools are continuously optimized to ensure that they can respond quickly and efficiently when real incidents occur.

[0410] In summary, the oral health management system in this application completely separates the functions of data collection and data analysis. The data collection toothbrush 10 is only responsible for efficiently and accurately collecting a variety of oral health data and adding a timestamp to each data point, while all complex data analysis is completed in the cloud. This functional separation design effectively reduces the hardware cost and energy consumption of the device, while making full use of the powerful computing power of the cloud to ensure the accuracy and speed of the analysis.

[0411] The oral health management system in this application transfers all data analysis tasks to the cloud. The system uses the elastic computing and large-scale data processing capabilities of the cloud to deeply integrate and analyze multimodal data. This architecture not only improves the efficiency of data processing, but also enables the system to cope with complex health management needs and provide accurate health assessments and personalized health recommendations.

[0412] Since the data collection toothbrush 10 in the present application does not undertake data processing tasks, its design is simplified, which reduces production and maintenance costs. This makes the device more portable, easy to use, and more competitive in price, while ensuring the accuracy and consistency of data collection. Although the data collection device itself has limited functions, the powerful data analysis capabilities of the cloud make up for this deficiency. By uploading data to the cloud in real time, the system can complete complex health analysis in a short time, provide timely health warnings and personalized suggestions, and help users improve health management.

[0413] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present application is described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present invention, all of which belong to the protection scope of the present invention.

Claims

1. An oral health management system, characterized in that: include: A toothbrush, the toothbrush comprising a main body and a brush head, the main body comprising a toothbrush end and a handheld end, a connecting portion being arranged at one side of the outer peripheral surface of the toothbrush end; the brush head comprising bristles and a base, the bristles being fixedly arranged on a side surface of the base, the base being detachably connected to the connecting portion so that the bristles extend in a direction away from the connecting portion; a plurality of data acquisition terminals are arranged around the connecting portion for acquiring oral information; A server, which is arranged in the cloud and is in communication with the toothbrush. After processing the oral information through big data technology, the oral information is analyzed by an artificial intelligence big model to obtain an analysis result; A human-computer interaction device is connected to the server for communication and issues prompt information according to the analysis result.

2. The oral health management system according to claim 1, characterized in that: Processing the oral information through big data technology includes: Remove noise from oral information.

3. The oral health management system according to claim 2, characterized in that: Processing the oral information through big data technology also includes: When the missing ratio of data columns or rows in the oral information exceeds a predetermined ratio, deletion processing is performed.

4. The oral health management system according to claim 3, characterized in that: Processing the oral information through big data technology also includes: When data columns or rows in the oral information are missing, the missing data are filled by using the mean or median after statistics, or by interpolation.

5. The oral health management system according to claim 1, characterized in that: The oral information includes at least one of image data, pressure data, temperature data, smell data and biological data in the oral cavity.

6. The oral health management system according to claim 5, characterized in that: The odor data has a higher priority than other data and is transmitted to the server first.

7. The oral health management system according to claim 5, characterized in that: Processing the oral information through big data technology also includes: The oral information is time synchronized and spatially aligned.

8. The oral health management system according to claim 1, characterized in that: The human-computer interaction device includes at least one of a mobile phone, a computer, and a tablet computer.

9. The oral health management system according to claim 1, characterized in that: The prompt information includes disease warning information and / or life behavior suggestions.

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