Children's oral health management system based on big data

Abstract

The present invention relates to the field of medical health and information technology, and specifically to a children's oral health management system based on big data, including: a data acquisition module, a data processing module, a data prediction module and a control module, wherein the data acquisition module includes an acquisition component and a collection device; when the predicted oral health condition is that the teeth cleanliness is not up to standard, the control module determines whether the vibration frequency matches according to the existing vibration frequency data of the electric toothbrush in the data acquisition module; when the predicted oral health condition is that the gums are red and swollen, the control module sends an instruction to the user's wearable health monitoring device to increase the number of oral cleaning times; when the predicted oral health condition is that bleeding occurs, the control module determines whether the cause of bleeding is caused by the electric toothbrush in the data acquisition module. The present invention is used to establish an accurate prediction model by integrating big data and artificial intelligence, so as to achieve comprehensive, accurate and personalized management of children's oral health.

Description

Technical Field

[0001] The present invention relates to the fields of medical health and information technology, and in particular to a children's oral health management system based on big data. Background Art

[0002] With the acceleration of the pace of modern life and changes in eating habits, children's oral health issues are increasingly receiving attention from parents and society. Traditional oral health management methods mainly rely on doctors' clinical experience and regular oral examinations, but this method has many shortcomings. For example, the frequency of regular oral examinations is limited, making it difficult to detect and deal with potential oral problems in a timely manner; at the same time, doctors' experience and subjective judgment may affect the accuracy and consistency of diagnostic results. In addition, parents' lack of knowledge about children's oral health and children's own lack of attention to oral hygiene are also important reasons for the frequent occurrence of children's oral health problems.

[0003] In recent years, the rapid development of big data and artificial intelligence technology has provided new solutions for oral health management. By collecting and analyzing a large amount of oral health data, an accurate prediction model can be established to monitor and warn children's oral health in real time, so as to detect and deal with potential oral problems in advance. However, most of the products for children's oral health management on the market currently have single functions and lack intelligent monitoring and management methods, which cannot meet the needs of parents and children for comprehensive and personalized oral health management services.

[0004] Therefore, there is an urgent need for a children's oral health management system that can comprehensively and accurately collect children's oral health data, use big data and artificial intelligence technology to establish an accurate prediction model, and provide personalized management and education services based on the predicted oral health status. Summary of the invention

[0005] To solve the above problems, the present invention provides a children's oral health management system based on big data, which is used to establish an accurate prediction model by integrating big data and artificial intelligence, so as to achieve comprehensive, accurate and personalized management of children's oral health.

[0006] In order to achieve the above purpose, the technical solution of the present invention is as follows: a children's oral health management system based on big data, comprising:

[0007] A data collection module is used to collect oral data of children. The collected oral data of children include but are not limited to medical records, living habits data and genetic information. The data collection module includes several collection components and collection equipment. The collection equipment is used to collect children's mouthwash and sample and test the mouthwash to assist in judging the health status of children's oral cavity;

[0008] The data processing module is used to pre-process the data collected by the data collection module, and the pre-processing includes data cleaning, data formatting, data normalization and data enhancement;

[0009] The data prediction module uses big data combined with artificial intelligence to establish a prediction model, obtains the data pre-processed by the data processing module through the prediction model, and predicts the oral health status of the child; the control module is used to trigger the early warning mechanism when the oral health status predicted by the data prediction module is not within the preset health status range, and adjust the data collection mode of the collection component according to the predicted oral health status;

[0010] The acquisition components include an electric toothbrush, an oral camera, and a wearable health monitoring device, and the electric toothbrush, the oral camera, and the wearable health monitoring device are all connected to the control module signal;

[0011] At that time, the control module determines whether the vibration frequency matches according to the current real-time vibration frequency data of the electric toothbrush in the data acquisition module;

[0012] If they do not match, the control module sends a command to the electric toothbrush to automatically adjust the vibration frequency;

[0013] If they match, the control module reminds the user to replace the toothbrush head;

[0014] When the predicted oral health condition is red and swollen gums, the control module sends an instruction to the user's wearable health monitoring device to increase the number of oral cleanings;

[0015] When the prediction result is that bleeding occurs, the control module determines whether the cause of the bleeding is the electric toothbrush in the data acquisition module;

[0016] If the cause of the bleeding is due to the electric toothbrush, the control module sends a command to the electric toothbrush to adjust the vibration frequency;

[0017] If the cause of the bleeding is not due to the electric toothbrush, the control module reminds the user to seek professional medical advice.

[0018] Furthermore, a temperature sensor, a pH sensor and a pressure sensor are installed on the top of the electric toothbrush, and the electric toothbrush, the temperature sensor, the pH sensor and the pressure sensor are all connected to the control module signal;

[0019] The temperature sensor is used to monitor the temperature inside the child's mouth in real time, the pH sensor is used to monitor the pH value inside the child's mouth in real time, the pressure sensor is used to monitor the pressure applied to the brush head of the electric toothbrush when the child is brushing his teeth in real time, and the control module is used to adjust the power of the electric toothbrush according to the oral health status predicted by the data prediction module and the real-time temperature, pH value and pressure applied to the brush head collected by the temperature sensor, pH sensor and pressure sensor.

[0020] Furthermore, an oral camera is installed on the top of the electric toothbrush, and the oral camera is used to capture the image data in the child's oral cavity, and is also used to combine with the brush head position information of the electric toothbrush;

[0021] The control module is used to combine the pressure data of the pressure sensor and the image data of the oral camera, judge the accuracy of the brushing position based on the pressure of the brush head, and assist in judging the health of the teeth contacted by the brush head.

[0022] Furthermore, it also includes a voice interaction module, which is used to collect children's voice feedback and provide interactive content for oral health education.

[0023] Furthermore, it also includes an intelligent reminder module, which is connected to the control module signal. The intelligent reminder module includes an indicator light and a buzzer. The indicator light and the buzzer are both embedded in the bottom of the electric toothbrush. The indicator light flashes and emits light of different colors to indicate different warning levels. The buzzer emits an alarm sound. After the controller triggers the warning mechanism, it sends an instruction to the intelligent reminder module, and the indicator light and the buzzer send corresponding warning information.

[0024] Furthermore, it also includes a personalized module, which is used to generate an oral health report and a personalized oral health improvement plan based on the child's oral health status, living habits, genetic information, historical data and the oral health status predicted by the data prediction module. The oral health improvement plan includes but is not limited to brushing time, frequency and intensity.

[0025] Furthermore, it also includes an intelligent reminder module, the intelligent reminder module signal is connected to the mobile terminal, and the intelligent reminder module is used to automatically send brushing reminders, oral examination reminders or health suggestions to the mobile terminal based on the child's oral health data and predicted oral health status.

[0026] Furthermore, it also includes a parent monitoring module, which is connected to the control module by signal, and is used to allow parents to view the oral health status, historical data and health reports of their children in real time.

[0027] Furthermore, it also includes a data storage module, which is used to automatically upload all collected and processed data to the cloud server for safe storage.

[0028] Furthermore, it also includes a data security and privacy protection module, which is responsible for ensuring the security and privacy of all children's oral health data collected, processed, stored and transmitted.

[0029] The technical principle of the above scheme is as follows: The system of the present invention integrates big data, artificial intelligence, the Internet of Things and mobile communication technologies, and collects children's oral health data in real time or regularly through multiple collection components (electric toothbrushes, oral cameras, wearable health monitoring devices, etc.). After preprocessing by the data processing module, these data are sent to the data prediction module. The data prediction module uses big data analysis and artificial intelligence algorithms to establish a prediction model to accurately predict the oral health status of children. According to the predicted oral health status, the control module will trigger the corresponding early warning mechanism and automatically adjust the working mode of the collection component to achieve personalized oral health management. At the same time, the system also provides a full range of oral health management and education services through voice interaction modules, personalization modules, intelligent reminder modules, parent monitoring modules, etc.

[0030] The above scheme has the following beneficial effects:

[0031] 1. This solution, through the data collection module, can comprehensively and accurately collect various types of children's oral data, including but not limited to oral imaging data, medical records, living habits data and genetic information. Compared with existing technologies, these data are more comprehensive and detailed, providing a more solid foundation for subsequent oral health prediction and management. Compared with existing technologies, traditional methods often only focus on a single oral health data, such as oral imaging or medical records, while this solution realizes the integration and analysis of multi-dimensional data, so as to more comprehensively evaluate children's oral health status.

[0032] 2. This solution achieves accurate response and personalized management of children's oral health problems through an intelligent control module. When the vibration frequency of the electric toothbrush does not match the predicted oral health status, the control module can automatically adjust the vibration frequency to a more appropriate range to ensure the best brushing effect and effectively avoid oral health problems caused by improper vibration frequency. At the same time, if the vibration frequency of the electric toothbrush matches the predicted condition but the cleaning effect is not good, the control module will promptly remind the user to replace the toothbrush head. This function not only improves the efficiency of the electric toothbrush, but also helps to maintain the cleanliness and hygiene of the toothbrush, further ensuring the oral health of children.

[0033] In addition, when the predicted oral health condition is red and swollen gums, the control module can send instructions to the user's wearable health monitoring device to increase the number of oral cleanings. This intelligent reminder function helps users adjust their oral cleaning habits in a timely manner to prevent further deterioration of gum problems. When bleeding occurs, the control module can quickly determine the cause of bleeding and send instructions to the electric toothbrush to adjust the vibration frequency or remind the user to seek professional medical advice based on the cause. This immediate response and personalized treatment strategy not only improves the efficiency of oral health management, but also helps users get correct treatment suggestions in a timely manner to avoid aggravating oral problems due to incorrect treatment.

[0034] 3. This solution uses big data and artificial intelligence technology to establish an accurate prediction model that can accurately predict children's oral health status. When the predicted oral health status is not within the preset health status range, the control module can trigger the early warning mechanism and adjust the data collection mode of the collection component according to the predicted oral health status, thereby realizing real-time monitoring and personalized management of children's oral health. Compared with existing technologies, traditional methods often rely on the doctor's experience and subjective judgment, while this solution improves the accuracy and efficiency of oral health management through scientific data analysis and prediction.

[0035] 4. This solution is also equipped with intelligent devices such as electric toothbrushes, temperature sensors, pH sensors and pressure sensors, which can monitor key parameters such as temperature, pH and brushing pressure in children's mouths in real time, and intelligently adjust the power of electric toothbrushes based on these data. This intelligent management method not only improves the efficiency and comfort of brushing, but also helps to cultivate good oral hygiene habits for children. Compared with existing technologies, traditional methods often lack intelligent monitoring and management methods, while this solution realizes intelligent management of children's oral health through the introduction of intelligent devices, improving the convenience and effectiveness of management.

[0036] 5. This solution also includes multiple functional modules such as personalization module, intelligent reminder module, parental monitoring module, data storage and data security and privacy protection module, which can provide users with personalized oral health improvement plans, intelligent reminder services, parental monitoring functions and secure data storage and privacy protection services. These functions not only improve the user experience, but also enhance the practicality and security of the system. Compared with the existing technology, traditional methods often have single functions and lack personalized and intelligent services. This solution provides users with comprehensive and intelligent oral health management services through the integration and collaborative work of multiple functional modules, meeting the needs and expectations of different users.

[0037] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a framework diagram of an embodiment of a children's oral health management system based on big data of the present invention;

[0039] Figure 2 It is a flow chart of an embodiment of a children's oral health management system based on big data of the present invention;

[0040] Figure 3 It is an overall framework diagram of an embodiment of the children's oral health management system based on big data of the present invention. DETAILED DESCRIPTION

[0041] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] The following is further described in detail through specific implementation methods:

[0043] Embodiment 1:

[0044] As attached Figure 1 , Figure 2 and Figure 3 Shown: Children's oral health management system based on big data, including:

[0045] The data collection module is used to collect data about the child's oral cavity. The collected data about the child's oral cavity includes but is not limited to medical records, living habits data and genetic information. The data collection module includes several collection components and collection devices. The collection devices are used to collect the child's mouthwash, sample and test the mouthwash, and assist in judging the health status of the child's oral cavity. The collection components include an electric toothbrush, an oral camera and a wearable health monitoring device. The electric toothbrush, the oral camera and the wearable health monitoring device are all connected to the control module signal: a temperature sensor, a pH sensor and a pressure sensor are installed on the top of the electric toothbrush. The electric toothbrush, the temperature sensor, the pH sensor and the pressure sensor are all connected to the control module signal. The temperature sensor is used to monitor the temperature in the child's oral cavity in real time. The pH sensor is used to monitor the pH value in the child's oral cavity in real time. The pressure sensor is used to monitor the brushing pressure in the child's oral cavity in real time. The control module is used to adjust the power of the electric toothbrush according to the oral health status predicted by the data prediction module and the real-time temperature, pH value and pressure on the brush head collected by the temperature sensor, pH sensor and pressure sensor. The oral camera is installed on the top of the electric toothbrush. The oral camera is used to capture image data inside the child's mouth and is also used to combine with the brush head position information of the electric toothbrush.

[0046] At the same time, the control module is used to combine the pressure data of the pressure sensor and the image data of the oral camera. For the area covered by foam during brushing (inaccurate image acquisition), the accuracy of the brushing position is judged based on the pressure of the brush head, and the health condition of the teeth contacted by the brush head is auxiliary judged, such as: normal morphology, no deformity, such as deformed lingual pits, deformed lingual cusps, deformed central cusps, etc.

[0047] When the predicted oral health condition is that the teeth cleanliness does not meet the standard, the control module determines whether the vibration frequency matches based on the current real-time vibration frequency data of the electric toothbrush in the data acquisition module; if it does not match, the control module sends an instruction to the electric toothbrush to automatically adjust the vibration frequency; if it matches, the control module reminds the user to replace the toothbrush head.

[0048] When the predicted oral health condition is red and swollen gums, the control module sends an instruction to the user's wearable health monitoring device to increase the number of oral cleaning times.

[0049] When the predicted oral health condition is bleeding, the control module determines whether the cause of bleeding is the electric toothbrush in the data acquisition module; if the cause of bleeding is the electric toothbrush, the control module sends an instruction to the electric toothbrush to adjust the vibration frequency; if the cause of bleeding is not the electric toothbrush, the control module reminds the user to seek professional medical advice.

[0050] The data processing module is used to pre-process the data collected by the data collection module, and the pre-processing includes data cleaning, data formatting, data normalization and data enhancement;

[0051] The data prediction module uses big data combined with artificial intelligence to establish a prediction model, obtains the data processed by the data processing module through the prediction model, and predicts the oral health status of children; the control module is used to trigger the early warning mechanism when the oral health status predicted by the data prediction module is not within the preset health status range, and adjust the data collection mode of the collection component according to the predicted oral health status.

[0052] It also includes a voice interaction module, which collects children's voice feedback, such as how they feel when brushing their teeth, their oral health status, etc. It provides interactive content for oral health education, such as oral health knowledge questions and answers, and guidance on brushing skills.

[0053] It also includes an intelligent reminder module, which is connected to the control module signal. The intelligent reminder module includes an indicator light and a buzzer. The indicator light and the buzzer are both embedded in the bottom of the electric toothbrush. The indicator light flashes and emits light of different colors to indicate different warning levels. The buzzer emits an alarm sound. After the controller triggers the warning mechanism, it sends an instruction to the intelligent reminder module, and the indicator light and the buzzer send corresponding warning information.

[0054] It also includes a personalized module, which is used to generate an oral health report and a personalized oral health improvement plan based on the child's oral health status, living habits, genetic information, historical data, and the oral health status predicted by the data prediction module. The oral health improvement plan includes but is not limited to brushing time, frequency, and intensity.

[0055] The specific implementation process is as follows: the electric toothbrush, oral camera and wearable health monitoring device included in the data acquisition module are installed and configured in the child's living environment. These devices are connected to the control module through wireless methods such as Bluetooth or Wi-Fi. A temperature sensor, pH sensor and pressure sensor are also installed on the top of the electric toothbrush, which also maintain signal connection with the control module. The oral camera captures the image data of the child's mouth when the electric toothbrush is in use or at specific time intervals.

[0056] Through user input or automatic import, the system records the child's oral medical history information, such as past medical records, treatment plans, and doctor's recommendations. Through user input, the system obtains the child's genetic information, such as family history of oral diseases. Wearable health monitoring devices (such as smart watches) record children's diet, sleep, exercise and other living habits data.

[0057] The data processing module preprocesses the data from the data acquisition module, including removing duplicate, erroneous and invalid data, converting the data into a unified format for subsequent processing and analysis, scaling the data to the same range, and eliminating dimensional effects. The integrity and richness of the data are enhanced by generating derived variables and filling in missing values.

[0058] The data prediction module uses big data and artificial intelligence technologies, such as machine learning (e.g. linear regression, which is suitable for scenarios where there is a linear relationship between the predicted value and multiple independent variables), to make predictions by establishing a linear relationship between independent variables (e.g. lifestyle habits, genetic information, etc.) and dependent variables (e.g. tooth cleanliness, gum health, etc.).

[0059] Alternatively, scenario logistic regression is suitable for predicting whether the oral health status is in a certain state (such as whether there is a risk of bleeding). It is mainly used for binary classification problems. The output of linear regression is converted into a probability value between 0 and 1 through the Sigmoid function to determine the probability that the sample belongs to a certain category) or deep learning algorithms. For example:

[0060] 1. Convolutional neural network (CNN) extracts image features and performs classification or regression prediction through structures such as convolutional layers, pooling layers, and fully connected layers. It is suitable for scenarios that process image data (such as oral imaging data), such as predicting dental lesions.

[0061] 2. Recurrent Neural Networks (RNNs) capture time dependencies in sequence data through recurrent connections. They are suitable for processing time series data (such as regular oral examination results), such as predicting the changing trend of oral health status in the future.

[0062] 3. Long Short-Term Memory (LSTM) is a variant of RNN. It solves the shortcomings of RNN in long-term dependency issues by introducing structures such as memory units and forget gates. It is suitable for processing long time series data and scenarios that need to capture long-term dependencies.

[0063] 4. Generative adversarial networks (GANs) generate realistic data samples through adversarial training between generators and discriminators. Although GANs are rarely used directly in oral health data prediction, they can be used to generate simulated data to enhance the training effect of the model or conduct oral disease simulation research) to establish a prediction model. During the model training process, historical oral health data is used as a training set, and the model parameters are optimized through continuous iteration. The data prediction module predicts the current oral health status of children after the data is processed by the data processing module. The predicted oral health status includes tooth cleanliness, gum health, bleeding risk, etc.

[0064] At the same time, a special container or receiving device is designed in the collection device, which is convenient for children to pour or spit mouthwash into it after rinsing their mouths. After collecting a sufficient amount of mouthwash, the system will take out a certain amount of mouthwash sample from the container, and the sampled mouthwash sample will be sent to the detection module of the system. The detection module detects and analyzes indicators such as microorganisms, chemical composition, pH value, etc. in the mouthwash. These indicators can reflect the health status of children's oral cavity, such as whether there is inflammation, infection or acid-base imbalance. The detection module compares the analysis results of the mouthwash sample with the preset health standards or reference data in the database to assist in judging the health status of children's oral cavity. If the test results are abnormal, the system may trigger an early warning mechanism to remind users or parents to pay attention to the oral health of children and recommend appropriate measures to improve them. When the predicted oral health condition is not within the preset health condition range, the control module triggers the early warning mechanism, such as sound or visual alarm (in this embodiment, the indicator light is designed to emit red, yellow and green lights, corresponding to different early warning levels. Red indicates a serious early warning, yellow indicates a medium early warning, and green indicates a normal or safe state. The buzzer is used to emit alarm sounds of different frequencies and volumes to help remind children.). According to the predicted oral health condition, the control module automatically adjusts the data collection mode of the collection component. As follows:

[0065] If the predicted oral health condition is that the teeth cleaning degree is not up to standard, the control module checks whether the vibration frequency of the electric toothbrush matches. If not, the vibration frequency is automatically adjusted to a more suitable range to ensure the best teeth cleaning effect. If it matches, the voice interaction module reminds the user to replace the toothbrush head. By automatically adjusting the vibration frequency of the electric toothbrush to a more suitable range, the teeth cleaning effect can be ensured to be optimal and the residue of dental plaque and food residue can be reduced.

[0066] If the predicted oral health condition is red and swollen gums, the control module sends instructions to the wearable health monitoring device to remind the user to increase the frequency of oral cleaning and recommend the use of specific oral care products. Through the voice interaction module, the system can improve the user experience and enable users to manage children's oral health more conveniently by reminding users to change toothbrush heads or increase the frequency of oral cleaning.

[0067] If the predicted oral health condition is bleeding, the control module analyzes the cause of the bleeding. If it is determined to be caused by an electric toothbrush, the vibration frequency is adjusted; if it is not caused by an electric toothbrush, the voice interaction module reminds the user to seek professional medical advice. The early warning mechanism can attract the attention of users or parents by issuing audible or visual alarms, increase their attention to children's oral health issues, and take necessary measures to improve them in a timely manner.

[0068] Based on the child's oral health status, living habits, genetic information, historical data, and the oral health status predicted by the data prediction module, the personalized module generates a detailed oral health report. According to the content of the report, a personalized oral health improvement plan is formulated, including specific recommendations on brushing time, frequency, and strength. For example, if a child has a tendency to tooth decay, the personalized module may recommend increasing the frequency of using fluoride toothpaste and remind parents to supervise their children's brushing process. If a child has sensitive gums, the personalized module may recommend using a soft toothbrush head and reducing the strength of brushing.

[0069] Finally, the control module fuses the pressure data of the pressure sensor and the image data of the oral camera. For areas covered by foam and resulting in inaccurate image acquisition, the system can make a preliminary judgment on the accuracy of the brushing position based on the pressure data of the brush head. If the brush head applies appropriate pressure at a certain position, and the position cannot be clearly displayed in the image due to foam, the system can infer that the brush head has indeed contacted the position. Through the analysis of pressure data, the system can further determine the contact between the brush head and the teeth. For example, if the brush head applies abnormally high pressure in a certain area, it may mean that there are abnormalities in the teeth in that area (such as caries, tartar, etc.), or the brushing method is incorrect (such as excessive force).

[0070] When the image data is relatively clear, the system can use image recognition technology to evaluate the morphology of the teeth. This includes checking whether the teeth are in normal shape, and whether there are abnormalities such as deformed lingual pits, deformed lingual cusps, and deformed central cusps. These deformities may affect the bite, chewing function, and aesthetics of the teeth. Combining pressure data and image data, the system can make a comprehensive judgment on the health of the teeth that the brush head contacts. If an abnormality is found, the system will generate a corresponding report or suggestion to remind the user or parent to pay attention and take corresponding measures to improve it.

[0071] Specific examples are as follows:

[0072] Example 1: Treatment of substandard tooth cleanliness

[0073] Xiao Ming, an 8-year-old boy, brushes his teeth twice a day with an electric toothbrush. However, the data prediction module predicts that his teeth cleanliness is not up to standard. The control module first checks the vibration frequency setting of the electric toothbrush and finds that it is currently set to "normal mode" (vibration frequency of 20,000 times per minute), but this frequency may not be enough based on Xiao Ming's oral health status and living habits (such as his love of sweets and short brushing time). Therefore, the control module automatically adjusts the vibration frequency to "enhanced mode" (25,000 times per minute) and recommends Xiao Ming to extend his brushing time to 2 minutes. By automatically adjusting the vibration frequency of the electric toothbrush to the "enhanced mode" that is more suitable for Xiao Ming, his teeth cleaning effect is significantly improved, and the residue of food residues and dental plaque is reduced. It is recommended that Xiao Ming extend his brushing time to 2 minutes and remind him to change the toothbrush head regularly, which helps to cultivate his good oral hygiene habits and lay the foundation for long-term oral health. After a week of observation, the data prediction module evaluates again and finds that Xiao Ming's teeth cleanliness has improved, but it still does not meet the optimal standard. At this time, the voice interaction module prompts Xiao Ming and his parents through gentle voice, suggesting that they replace the toothbrush head with one designed specifically for children with better cleaning effects.

[0074] Example 2: Treatment of red and swollen gums

[0075] Xiaohua, a 10-year-old girl, has recently been under great academic pressure and often stays up late at night, resulting in incomplete oral cleaning. The data prediction module predicts that her gums show signs of redness and swelling. The control module immediately sends a reminder to the wearable health monitoring device worn by Xiaohua, suggesting that she add one oral cleaning per day, that is, brush her teeth after dinner. At the same time, the system also recommends oral care products containing antibacterial ingredients, such as mouthwash and toothpaste, to help relieve red and swollen gums. After Xiaohua followed the advice, the redness and swelling of her gums were significantly relieved within a few days. The advice provided by the system helps Xiaohua improve her oral cleaning habits, reduce the risk of recurrence of red and swollen gums, and maintain oral health. The reminders from the wearable health monitoring device have increased Xiaohua's attention to oral health and prompted her to pay more attention to her oral hygiene.

[0076] Example 3: Management of bleeding

[0077] Xiaoqiang, a 7-year-old boy, suddenly started bleeding while brushing his teeth. The data prediction module quickly identified this anomaly, and the control module immediately analyzed the cause of the bleeding. By checking the usage records of the electric toothbrush, it was found that Xiaoqiang was brushing his teeth too hard and the vibration frequency of the electric toothbrush was set high. The control module automatically adjusted the vibration frequency to "gentle mode" (15,000 times per minute), and reminded Xiaoqiang through the voice interaction module to use the correct brushing method, that is, to gently move the toothbrush on the surface of the teeth to avoid excessive force. At the same time, the system also recommends that Xiaoqiang moisten his mouth with warm water before brushing his teeth to reduce irritation when brushing his teeth. If the bleeding continues, the system also reminds Xiaoqiang and his parents through the voice interaction module to seek professional medical advice as soon as possible.

[0078] Example 4: Development of a personalized oral health improvement plan

[0079] Xiaoli, a 9-year-old girl, is prone to tooth decay. The personalized module developed a detailed oral health improvement plan for her based on her oral health status, lifestyle, genetic information, and historical data. The plan recommends that Xiaoli brush her teeth at least twice a day with fluoride toothpaste, each time for no less than 2 minutes; at the same time, it reminds her to avoid sugary foods and drinks before going to bed. In addition, the personalized module also recommends that Xiaoli have regular oral examinations to detect and deal with any potential oral problems in a timely manner. By following this plan, Xiaoli's risk of tooth decay has been effectively controlled.

[0080] Xiaojie, a 6-year-old boy, has sensitive gums. The oral health improvement plan generated by the personalized module for him emphasizes the importance of using a soft toothbrush head and reducing the force of brushing. The plan also recommends Xiaojie to wet the toothbrush and mouth with warm water before brushing to reduce irritation when brushing. At the same time, the system also recommends some oral care products designed for sensitive gums, such as alcohol-free mouthwash and mild formula toothpaste. By following this plan, Xiaojie's gum sensitivity problem has been significantly improved.

[0081] Embodiment 2:

[0082] As attached Figure 3 As shown, the difference from Example 1 is that it also includes an intelligent reminder module, and the intelligent reminder module signal is connected to the mobile terminal. The intelligent reminder module is used to automatically send brushing reminders, oral examination reminders or health suggestions to the mobile terminal (such as mobile phones, tablets, etc.) based on the child's oral health data and predicted oral health status.

[0083] It also includes a parent monitoring module, which is connected to the control module signal, and is used to allow parents to view the child's oral health status, historical data and health reports in real time.

[0084] The specific implementation process is as follows: The intelligent reminder module receives information from the data prediction module and the control module, and analyzes the child's oral health status and predicted oral health status. According to the analysis results, corresponding reminders or suggestions are generated. Through signal connection, the intelligent reminder module sends the generated reminders or suggestions to the mobile terminal of the parent or child. The reminder content may include brushing time, oral examination date, suggestions for using specific oral care products, etc. Parents can set the frequency, time and content of reminders in the system according to the actual situation of the child to ensure the accuracy and effectiveness of the reminders.

[0085] The parent monitoring module is connected to the control module signal to obtain the child's oral health data, historical records and predicted oral health status. Parents can view these detailed information by logging into the system. The system provides real-time monitoring functions, and parents can check their children's brushing conditions, oral cleanliness, gum health, etc. at any time. At the same time, the system will also regularly generate health reports for parents' reference. Parents can interact with the system through the parent monitoring module, such as submitting additional information on their children's oral health, seeking professional advice, or adjusting system settings. The system will make corresponding adjustments and optimizations based on parents' feedback.

[0086] Embodiment 3:

[0087] As attached Figure 3 As shown, the difference from Example 2 is that it also includes a data storage module, which is used to automatically upload all collected and processed data to the cloud server for safe storage. This includes oral imaging data, medical records, lifestyle data, genetic information, and predicted oral health status and health reports.

[0088] It also includes a data security and privacy protection module, which is responsible for ensuring the security and privacy of all children's oral health data collected, processed, stored and transmitted. This includes data encryption, access control, data transmission security, and privacy policy formulation.

[0089] The specific implementation process is as follows: After the data acquisition module and processing module complete the data acquisition and preprocessing, the data storage module will automatically upload the data to the cloud server. The cloud server provides data backup function to ensure that the data can be quickly restored in unexpected situations. At the same time, the system also regularly performs data integrity checks to ensure the accuracy and integrity of the data. The data storage module strictly controls the access rights of the data, and only authorized users (such as parents, doctors and system administrators) can access the relevant data.

[0090] The present invention uses advanced encryption algorithms to encrypt the stored and transmitted data to ensure that the data is not stolen or tampered with during the transmission process. The system controls the access rights of different users to the data through strict identity authentication and permission management mechanisms. Only authorized users can access, modify or delete relevant data. The system uses secure communication protocols (such as HTTPS) to ensure the security and privacy of data during transmission. The system formulates a clear privacy policy to clearly inform users of the data collection, processing, storage and transmission methods, as well as the rights and obligations of users. At the same time, the system also regularly reviews and updates the privacy policy to adapt to changes in laws and regulations and changes in user needs.

[0091] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. A children's oral health management system based on big data, characterized by: include: A data collection module is used to collect oral data of children. The collected oral data of children include but are not limited to medical records, living habits data and genetic information. The data collection module includes several collection components and collection equipment. The collection equipment is used to collect children's mouthwash and sample and test the mouthwash to assist in judging the health status of children's oral cavity; The data processing module is used to pre-process the data collected by the data collection module, and the pre-processing includes data cleaning, data formatting, data normalization and data enhancement; The data prediction module uses big data combined with artificial intelligence to establish a prediction model, and uses the prediction model to obtain the data pre-processed by the data processing module to predict the oral health status of children; A control module, used to trigger an early warning mechanism when the oral health status predicted by the data prediction module is not within a preset health status range, and to adjust a data collection mode of the collection component according to the predicted oral health status; The acquisition components include an electric toothbrush, an oral camera, and a wearable health monitoring device, and the electric toothbrush, the oral camera, and the wearable health monitoring device are all connected to the control module signal; The control module is used to determine whether the vibration frequency matches according to the current real-time vibration frequency data of the electric toothbrush in the data acquisition module when the predicted oral health condition is that the teeth cleanliness is not up to standard; If they do not match, a command is sent to the electric toothbrush to automatically adjust the vibration frequency; If they match, the user is reminded to replace the toothbrush head; When the predicted oral health condition is red and swollen gums, the control module sends an instruction to the user's wearable health monitoring device to increase the number of oral cleanings; When the predicted oral health condition is bleeding, the control module determines whether the cause of the bleeding is the electric toothbrush in the data acquisition module; If the cause of the bleeding is due to the electric toothbrush, the control module sends a command to the electric toothbrush to adjust the vibration frequency; If the cause of bleeding is not due to the electric toothbrush, the control module reminds the user to seek professional medical advice; Also included is a personalization module, which is used to generate an oral health report and a personalized oral health improvement plan based on the child's oral health status, living habits, genetic information, historical data, and the oral health status predicted by the data prediction module, wherein the oral health improvement plan includes but is not limited to brushing time, frequency, and intensity; It also includes a parent monitoring module, which is connected to the control module signal, and is used to allow parents to view the child's oral health status, historical data and health reports in real time.

2. The children's oral health management system based on big data according to claim 1 is characterized in that: A temperature sensor, a pH sensor and a pressure sensor are installed on the top of the electric toothbrush, and the electric toothbrush, the temperature sensor, the pH sensor and the pressure sensor are all connected to the control module signal; The temperature sensor is used to monitor the temperature inside the child's mouth in real time, the pH sensor is used to monitor the pH value inside the child's mouth in real time, the pressure sensor is used to monitor the pressure applied to the brush head of the electric toothbrush when the child is brushing his teeth in real time, and the control module is used to adjust the power of the electric toothbrush according to the oral health status predicted by the data prediction module and the real-time temperature, pH value and pressure applied to the brush head collected by the temperature sensor, pH sensor and pressure sensor.

3. The children's oral health management system based on big data according to claim 2 is characterized in that: The oral camera is installed on the top of the electric toothbrush. The oral camera is used to capture the image data inside the child's mouth and is also used to combine with the brush head position information of the electric toothbrush; The control module is used to combine the pressure data of the pressure sensor and the image data of the oral camera, judge the accuracy of the brushing position based on the pressure of the brush head, and assist in judging the health of the teeth contacted by the brush head.

4. The children's oral health management system based on big data according to claim 3 is characterized in that: It also includes a voice interaction module, which is used to collect children's voice feedback and provide interactive content for oral health education.

5. The children's oral health management system based on big data according to claim 4 is characterized in that: It also includes an intelligent reminder module, which is connected to the control module signal. The intelligent reminder module includes an indicator light and a buzzer. The indicator light and the buzzer are both embedded in the bottom of the electric toothbrush. The indicator light flashes and emits light of different colors to indicate different warning levels. The buzzer emits an alarm sound. After the controller triggers the warning mechanism, it sends an instruction to the intelligent reminder module, and the indicator light and the buzzer send corresponding warning information.

6. The children's oral health management system based on big data according to claim 5 is characterized in that: It also includes an intelligent reminder module, the signal of which is connected to a mobile terminal. The intelligent reminder module is used to automatically send brushing reminders, oral examination reminders or health suggestions to the mobile terminal based on the child's oral health data and predicted oral health status.

7. The children's oral health management system based on big data according to claim 6 is characterized in that: It also includes a data storage module, which is used to automatically upload all collected and processed data to the cloud server for secure storage.

8. The children's oral health management system based on big data according to claim 7 is characterized in that: It also includes a data security and privacy protection module, which is responsible for ensuring the security and privacy of all children's oral health data collected, processed, stored and transmitted.

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