Oral health management system based on big data

Abstract

The invention relates to the technical field of oral health management, and discloses an oral health management system based on big data, which comprises a data acquisition module, a data processing module and a data processing module, the intelligent diagnosis module is used for identifying oral health problems and diagnosing oral diseases through deep learning and an artificial intelligence algorithm, the health management suggestion module is used for predicting the future oral health trend of a user based on historical health data according to an intelligent diagnosis result, and the intelligent prediction module is used for predicting the future oral health trend of the user based on the historical health data. And the remote diagnosis and treatment module is used for providing auxiliary services for remote dental diagnosis and treatment. Through a data acquisition module, a data fusion module and an intelligent diagnosis module, oral cavity data and medical image data of a user are integrated, so that formulation of a personalized health management scheme is achieved, personalized oral cavity nursing schemes, diet guidance and living habit adjustment suggestions are provided for each user, and the user experience is improved. Therefore, the accuracy and effect of oral health management are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oral health management, and specifically to a big data-based oral health management system. Background Art

[0002] At present, oral health management has entered an era of informatization and intelligence. With the development of intelligent devices and big data technology, the collection and analysis of oral health data have gradually become possible. Existing oral health management systems mainly rely on traditional dental examination and diagnosis tools, and provide oral care suggestions for users through manual evaluation. These traditional methods can provide basic health management services to a certain extent, but there are limitations in terms of personalization and accuracy.

[0003] In many oral health management systems, there is a lack of comprehensive analysis of the relationship between users' daily living habits (such as diet, exercise, sleep, etc.) and oral health, resulting in relatively single health management plans, which are difficult to meet the personalized needs of different users. In addition, most existing oral health management systems only rely on basic dental examinations and imaging equipment, and do not fully utilize big data and deep learning algorithms to deeply analyze multi-modal data (including oral health data, medical imaging data, and living habit data). Therefore, there is still much room for improvement in the accuracy, personalization, and real-time nature of the oral health management plans of existing systems.

[0004] Most existing oral health management systems rely on manual examinations and standardized health suggestions, mostly relying on manual or simple equipment for diagnosis, and cannot effectively integrate data from different sensors, imaging equipment, and users' life behaviors. This leads to relatively rough formulation of health management plans, lack of accurate health assessment and problem prediction, and failure to provide highly personalized management plans based on users' specific health data such as personal oral conditions and living habits, and cannot meet the diverse needs of different users in terms of oral care, diet, and adjustment of living habits. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a big data-based oral health management system, which solves the problems that it cannot meet the diverse needs of different users in terms of oral care, diet, and adjustment of living habits, cannot effectively integrate data from different sensors, imaging equipment, and users' life behaviors, resulting in relatively rough formulation of health management plans, lack of accurate health assessment and problem prediction.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A big data-based oral health management system, comprising: Data acquisition module, data fusion module, oral examination module, intelligent diagnosis module, health management advice module, real-time monitoring and feedback module, personalized recommendation module, intelligent prediction module, and remote diagnosis and treatment module; The data acquisition module is used to collect various data related to the oral cavity from the acquisition device; The data fusion module is used to integrate and process multi-modal data from different sources; The oral examination module is used to detect the inner wall of the oral cavity and teeth and collect the detection result data; The intelligent diagnosis module is used to identify and diagnose oral diseases through deep learning and artificial intelligence algorithms; The health management advice module is used to provide personalized oral health management advice for users according to the intelligent diagnosis results; The real-time monitoring and feedback module is used to track the oral health status of users in real time and send feedback and suggestions to users in a timely manner through edge devices; The personalized recommendation module is used to provide personalized health management solutions for users according to the health assessment results and prediction data; The intelligent prediction module is used to predict the future oral health trends of users based on historical health data; The remote diagnosis and treatment module is used to provide auxiliary services for remote dental diagnosis and treatment.

[0007] Preferably, the data acquisition module includes an oral health data acquisition unit, a lifestyle data acquisition unit, and a medical image data acquisition unit. The oral health data acquisition unit is used to collect data on tooth surface cleanliness, tooth wear, and gum health through an intelligent toothbrush and oral sensor devices. The lifestyle data acquisition unit is used to collect users' diet, exercise, and sleep lifestyle data through user intelligent devices, and the intelligent devices include mobile applications or wearable devices. The medical image data acquisition unit is used to collect users' oral image data through oral imaging devices. The various data of the oral cavity include oral health data, lifestyle data, and medical image data.

[0008] Preferably, the data fusion module includes a data cleaning unit, a multi-modal data fusion unit, and a data analysis unit. The data cleaning unit is used to denoise, fill in missing values, and format various collected data. The multi-modal data fusion unit is used to fuse multi-modal information from different sensors, images, and behavior data to generate a complete oral health data model. The data analysis unit is used to analyze the fused data to identify potential oral health problems. The integration and processing include data cleaning, denoising, and formatting.

[0009] Preferably, the oral detection module includes a dental caries detection unit, a periodontal disease detection unit, and a tooth wear detection unit. The dental caries detection unit is used to detect the condition of tooth decay, the periodontal disease detection unit is used to detect the health status of periodontal tissues, and the tooth wear detection unit is used to detect the degree of tooth wear.

[0010] Preferably, the intelligent diagnosis module includes a disease identification unit, a personalized diagnosis unit, and a risk assessment unit. The disease identification unit automatically identifies oral diseases by performing in-depth learning analysis on the collected oral image data and health data. The personalized diagnosis unit is used to provide personalized oral health diagnoses and suggestions for each user based on the user's oral health status and living habits. The risk assessment unit is used to evaluate the oral health risks of users based on their health records, combined with historical data and disease occurrence probability models. The oral diseases include dental caries and periodontitis.

[0011] Preferably, the health management advice module includes an oral care advice unit, a diet advice unit, and a living habit adjustment unit. The oral care advice unit is used to provide users with personalized oral care plans through intelligent diagnosis results. The oral care plans include brushing techniques, dental floss use, and mouthwash. The diet advice unit is used to provide diet guidance that is beneficial to oral health based on the user's eating habits. The diet guidance includes reducing sugar intake or increasing calcium-rich foods. The living habit adjustment unit is used to provide improvement suggestions in terms of exercise and sleep based on the user's living habit data to promote oral health. The oral health management advice includes oral care methods, diet advice, and living habit adjustments.

[0012] Preferably, the real-time monitoring and feedback module includes a health data monitoring unit, an anomaly detection and alarm unit, and a feedback and advice unit. The health data monitoring unit is used to monitor the user's oral health data in real time and synchronize the data to the system cloud. The oral health data includes tooth cleanliness and the condition of gum bleeding. The anomaly detection and alarm unit is used to automatically detect oral health anomalies of users and trigger alarms based on real-time monitoring data, reminding users to take corresponding measures. The feedback and advice unit is used to provide real-time feedback to users through mobile devices, enabling users to take intervention measures in a timely manner after discovering problems. The edge devices include smart watches, mobile phones, and fitness trackers.

[0013] Preferably, the personalized recommendation module includes a health management plan generation unit, a lifestyle suggestion unit, and an oral care reminder unit. The health management plan generation unit generates a personalized oral health management plan based on the health assessment results. The lifestyle suggestion unit provides lifestyle suggestions for improving oral health according to the user's health condition. The oral care reminder unit provides regular oral care reminders according to the user's health condition.

[0014] Preferably, the intelligent prediction module includes a prediction model training unit, a health trend prediction unit, and a personalized prediction adjustment unit. The prediction model training unit is used to train an oral health prediction model based on historical health data. The health trend prediction unit is used to predict the trend of the user's future oral health condition according to the prediction model. The personalized prediction adjustment unit adjusts the prediction result according to the user's specific data.

[0015] Preferably, the remote diagnosis and treatment module includes a video diagnosis and treatment unit, a remote diagnosis unit, and a prescription management unit. The video diagnosis and treatment unit is used to provide remote diagnosis and treatment services through video conferencing. The remote diagnosis unit is used to conduct remote diagnosis through the collected data and images. The prescription management unit is used to issue oral health-related prescriptions according to the diagnosis results and manage electronic prescriptions.

[0016] The present invention provides an oral health management system based on big data, having the following beneficial effects: 1. Through the data collection module, data fusion module, and intelligent diagnosis module, the present invention integrates the user's oral data and medical image data, achieving the formulation of a personalized health management plan, providing a personalized oral care plan, diet guidance, and lifestyle adjustment suggestions for each user, thereby improving the accuracy and effectiveness of oral health management.

[0017] 2. Through the real-time monitoring and feedback module, the present invention can monitor the user's oral health data in real time, and synchronize the data to the cloud through the health data monitoring unit. Once it is found that the tooth cleanliness is too low or there is gum bleeding, the system automatically triggers an alarm through the anomaly detection and alarm unit and feeds it back to the user in a timely manner through a mobile device, helping the user take intervention measures as early as possible to avoid the further deterioration of the condition.

[0018] 3. Through the data fusion module, the system can fuse multi-modal information from different sensors, medical imaging devices, and user behavior data. These data are transmitted to the data cleaning unit for denoising, filling missing values, and formatting, and then integrated into a unified oral health data model by the multi-modal data fusion unit. The data analysis unit further analyzes the fused data to identify potential oral health problems, providing support for the intelligent diagnosis module to quickly judge the oral health status. Brief Description of the Drawings

[0019] Figure 1 is a perspective view of an oral health management system based on big data according to the present invention; Figure 2 is an architecture diagram of a data acquisition module of an oral health management system based on big data according to the present invention; Figure 3 is a relationship architecture diagram of a data acquisition module of an oral health management system based on big data according to the present invention; Figure 4 is an architecture diagram of a data fusion module of an oral health management system based on big data according to the present invention; Figure 5 is a relationship architecture diagram of a data fusion module of an oral health management system based on big data according to the present invention; Figure 6 is an architecture diagram of an oral examination module of an oral health management system based on big data according to the present invention; Figure 7 is a relationship architecture diagram of an oral examination module of an oral health management system based on big data according to the present invention; Figure 8 is an architecture diagram of an intelligent diagnosis module of an oral health management system based on big data according to the present invention; Figure 9 is a relationship architecture diagram of an intelligent diagnosis module of an oral health management system based on big data according to the present invention; Figure 10 is an architecture diagram of a health management advice module of an oral health management system based on big data according to the present invention; Figure 11 is an architecture diagram of a real-time monitoring and feedback module of an oral health management system based on big data according to the present invention; Figure 12 is an architecture diagram of a personalized recommendation module of an oral health management system based on big data according to the present invention; Figure 13 is a relationship architecture diagram of an intelligent diagnosis module of an oral health management system based on big data according to the present invention; Figure 14 is an architecture diagram of an intelligent prediction module of an oral health management system based on big data according to the present invention; Figure 15 is a relationship architecture diagram of an intelligent prediction module of an oral health management system based on big data according to the present invention; Figure 16 is an architecture diagram of a remote diagnosis and treatment module of an oral health management system based on big data according to the present invention; Figure 17 is a relationship architecture diagram of a remote diagnosis and treatment module of an oral health management system based on big data according to the present invention. Detailed implementation mode

[0020] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] Please refer to the attached Figure 1 - attached Figure 17 , the embodiment of the present invention provides an oral health management system based on big data, including: A data collection module, a data fusion module, an oral examination module, an intelligent diagnosis module, a health management advice module, a real-time monitoring and feedback module, a personalized recommendation module, an intelligent prediction module, and a remote diagnosis and treatment module; The data collection module is used to collect various data related to the oral cavity from the collection device; The data fusion module is used to integrate and process multi-modal data from different sources; The oral examination module is used to detect the inner wall of the oral cavity and teeth and collect the detection result data; The intelligent diagnosis module is used to identify and diagnose oral diseases through deep learning and artificial intelligence algorithms; The health management advice module is used to provide personalized oral health management advice for users according to the intelligent diagnosis results; The real-time monitoring and feedback module is used to track the oral health status of users in real time and send feedback and suggestions to users in a timely manner through edge devices; The personalized recommendation module is used to provide personalized health management solutions for users according to the health assessment results and prediction data; The intelligent prediction module is used to predict the future oral health trends of users based on historical health data; The remote diagnosis and treatment module is used to provide auxiliary services for remote dental diagnosis and treatment.

[0022] The data collection module includes an oral health data collection unit, a living habit data collection unit, and a medical image data collection unit. The oral health data collection unit is used to collect data on the cleanliness of the tooth surface, tooth wear, and gum health through an intelligent toothbrush and an oral sensor device. The living habit data collection unit is used to collect data on the user's diet, exercise, and sleep living habits through the user's intelligent device. The intelligent device includes a mobile application or a wearable device. The medical image data collection unit is used to collect the user's oral image data through an oral imaging device. The various data of the oral cavity include oral health data, living habits, and medical image data.

[0023] Specifically, the oral health data acquisition unit can monitor the user's oral health in real time by connecting to a smart toothbrush and oral sensor devices. The smart toothbrush can monitor the cleanliness of the tooth surface through built-in sensors, including the brushing force, time, and position, helping the user optimize their brushing habits, thereby effectively reducing the occurrence of oral problems such as gum bleeding and dental caries. The oral sensor device can monitor the tooth wear degree and judge whether the user has bad occlusion or bruxism habits by evaluating the wear condition of the tooth surface, providing early warning for tooth health. The gum health data is also collected in real time through sensors, which can provide important information about the gum status (such as gum bleeding, swelling, etc.), providing a basis for further diagnosis; The lifestyle data acquisition unit collects the user's lifestyle data such as diet, exercise, and sleep through integrated smart devices, including but not limited to smartphone applications and wearable devices. The smartphone application can record the user's eating habits, capture their daily diet content, food types, and nutritional components, thereby evaluating its impact on oral health. Wearable devices (such as smart bracelets or smartwatches) can monitor the user's exercise amount, exercise habits, and sleep quality, etc., helping to analyze the indirect impact of lifestyle on oral health. Through this multi-dimensional lifestyle data acquisition, the system can provide personalized health management suggestions for users, improve bad habits, and thus optimize oral health; The medical imaging data acquisition unit performs image acquisition on the user's oral cavity through oral imaging devices (such as oral endoscopes, X-ray machines, etc.) to achieve a comprehensive examination of structures such as teeth, periodontal tissues, and the inner wall of the oral cavity. The medical imaging data acquisition unit can detail the morphology of teeth, the health status of the periodontium, and possible diseases such as dental caries and periodontitis through high-resolution imaging technology. These image data will be used as basic input data for further analysis and processing by the subsequent intelligent diagnosis module, health management advice module, etc. of the system. Through the comprehensive data acquisition method, not only the accuracy of oral health management is improved, but also a full-range health management platform is provided for users, contributing to the prevention, treatment, and management of oral health.

[0024] The data fusion module includes a data cleaning unit, a multi-modal data fusion unit, and a data analysis unit. The data cleaning unit is used to denoise, fill in missing values, and format various types of collected data. The multi-modal data fusion unit is used to fuse multi-modal information from different sensors, images, and behavioral data to generate a complete oral health data model. The data analysis unit is used to analyze the fused data to identify potential oral health problems, integrating and processing including data cleaning, denoising, and formatting.

[0025] Specifically, the data cleaning unit preprocesses various types of collected data to ensure data quality and consistency. The data cleaning unit includes functions such as denoising, filling missing values, and formatting. The denoising process uses advanced signal processing algorithms, such as wavelet transform, mean filtering, or Gaussian filtering, to remove noise interference in sensor data and image data, ensuring data accuracy. For missing values in sensor and image data, the data cleaning unit uses interpolation algorithms (such as linear interpolation, KNN interpolation, or time series-based interpolation methods) to fill in the missing parts, ensuring data integrity. Data formatting processes standardize different types of data into a unified format for subsequent data fusion and analysis; In the oral health management system, the multi-modal data fusion unit integrates data from multiple sensors, imaging devices, and user behavior data, involving different data modalities, such as oral health data, lifestyle data, and medical image data. The core function of the multi-modal data fusion unit is to integrate these multi-modal data from different sources to generate a complete oral health data model. Fusion methods include, but are not limited to, data dimensionality reduction based on feature selection and dimensionality reduction techniques (such as principal component analysis PCA, t-SNE, etc.) to reduce data dimensions and improve fusion efficiency, and deep learning methods such as weighted average and convolutional neural network (CNN) to perform weighted fusion on data of different modalities, match sensor data with image data, and generate a unified health data model. This data model will contain comprehensive information on the user's oral health, providing support for subsequent intelligent diagnosis and health advice; The data analysis unit deeply analyzes the data after cleaning and fusion to identify potential oral health problems. The data analysis unit uses advanced machine learning and deep learning technologies, including algorithms such as support vector machine (SVM), decision tree, random forest, and convolutional neural network (CNN), and combines the characteristics of multi-modal data to identify and predict oral diseases. The system can predict the occurrence risk of oral diseases such as dental caries and periodontitis by analyzing data such as tooth wear and gum health status; at the same time, by analyzing the user's lifestyle data (such as diet, sleep, exercise, etc.), it evaluates its impact on oral health to identify possible health problems. The data analysis unit can also establish an oral health risk assessment model based on the user's health records and historical data to evaluate the probability of an individual getting sick in a certain period in the future, providing early warning and intervention suggestions. In the process of use, this can not only improve the accuracy and personalization of oral health management, but also enhance the intelligent level and user experience of the system.

[0026] The oral detection module includes a dental caries detection unit, a periodontal disease detection unit, and a tooth wear detection unit. The dental caries detection unit is used to detect the condition of tooth decay. The periodontal disease detection unit is used to detect the health status of the periodontal tissue. The tooth wear detection unit is used to detect the degree of tooth wear.

[0027] Specifically, the dental caries detection unit mainly combines oral imaging data and sensor data, and uses image processing and machine learning technologies to automatically identify signs of dental caries on teeth. The user uses a smart toothbrush equipped with a built-in sensor or other detection devices to comprehensively scan the teeth and collect tooth surface image data. The dental caries detection unit uses image processing algorithms (such as edge detection, morphological processing, etc.) to process the tooth images, extracts the characteristic information of the dental caries area, and analyzes and determines it through a trained deep learning model (such as a convolutional neural network CNN), so as to determine the presence and degree of dental caries. At the same time, the pH value change of the teeth can be detected in real time through wearable devices (such as smart tooth detectors or oral sensors). The dental caries detection unit can also combine these data and further improve the accuracy and sensitivity of detection through technologies such as threshold judgment and pattern recognition; The periodontal disease detection unit mainly detects the health status of the periodontal tissue, with a focus on monitoring the health status of the gums, periodontal ligaments, and alveolar bone. The periodontal disease detection unit mainly uses oral imaging devices (such as oral endoscopes, X-ray machines, etc.) to collect high-definition images or imaging data of the user's periodontal area. Then, image processing technology is used to analyze key features such as the color, thickness of the gums, and density of the alveolar bone to determine whether there are diseases such as periodontitis, periodontal bleeding, or alveolar bone resorption, including digital imaging analysis technologies such as computer-aided diagnosis (CAD) systems, which automatically analyze the symptoms and early signs of periodontal disease through algorithms, such as gum redness, bleeding, atrophy, etc. In addition, this unit can also combine the user's clinical data (such as periodontal pocket depth, gum bleeding, etc.), and through multi-dimensional data fusion, evaluate the severity and risk of periodontal disease, and provide personalized prevention and treatment suggestions; The tooth wear detection unit is used to detect the wear degree of the user's teeth. Tooth wear is usually caused by improper occlusion, excessive brushing, improper chewing, or long-term teeth grinding, etc. Early detection of tooth wear problems helps to take protective measures in a timely manner. The tooth wear detection unit uses ultrasonic sensors or high-precision imaging devices to collect the surface morphology and wear degree of the user's teeth, and performs high-precision modeling of the tooth surface through three-dimensional imaging technologies (such as laser scanning, optical scanning, etc.). Subsequently, by comparing the current state of the user's teeth with the normal tooth morphology, the detection unit can accurately calculate the wear degree of the teeth. Combining machine learning algorithms, the tooth wear detection unit can also analyze the user's occlusion pattern and the oral care tools used (such as toothbrush type and strength), thereby further evaluating the causes of tooth wear and proposing improvement measures. Through the oral detection module, it is possible to achieve all-round monitoring of oral health, providing early health warnings and precise treatment plans for users.

[0028] The intelligent diagnosis module includes a disease identification unit, a personalized diagnosis unit, and a risk assessment unit. The disease identification unit automatically identifies oral diseases through in-depth learning analysis of the collected oral imaging data and health data. The personalized diagnosis unit is used to provide personalized oral health diagnoses and suggestions for each user based on the user's oral health status and living habits. The risk assessment unit is used to evaluate the oral health risks of users based on the user's health records, combined with historical data and disease occurrence probability models. Oral diseases include dental caries and periodontitis.

[0029] Specifically, the main function of the disease identification unit is to automatically identify and diagnose oral diseases through in-depth learning analysis of the collected oral imaging data and health data. The disease identification unit obtains the user's oral image data through high-precision imaging acquisition devices (such as digital oral imaging, oral endoscopes, etc.). These data include, but are not limited to, images of teeth, gums, periodontium, and oral soft tissues. Subsequently, image recognition algorithms such as convolutional neural networks (CNNs) in deep learning technology are used to automatically analyze various signs of oral diseases in the images, such as dental caries, periodontitis, dental calculus, tooth defects, etc. To improve the accuracy of disease identification, the system will use a large amount of historical data to train the model, automatically mark and learn the characteristics of different oral diseases, ensuring efficient and accurate disease identification on new user data. Through layer-by-layer feature extraction and pattern matching of the imaging data, the deep learning model can achieve efficient diagnosis of complex oral diseases, with high accuracy and reliability.

[0030] The main task of the personalized diagnosis unit is to provide personalized oral health diagnoses and recommendations for each user based on their specific oral health conditions and lifestyle habits. It will combine the user's health records, lifestyle data (such as diet, sleep, exercise, etc.) and medical examination data, and comprehensively evaluate the user's health status through an algorithm model. Based on this model, the system will analyze the user's health trends and risks, predict possible disease developments, and formulate personalized diagnosis plans and health management recommendations in combination with the user's specific circumstances (such as age, gender, genetic information, etc.). It can help users understand their current oral health status and potential risks, so as to take targeted preventive or treatment measures to ensure that each user can obtain a health plan that meets their individual needs; The main function of the risk assessment unit is to assess the oral health risks of users by combining their health records, historical data, and disease occurrence probability models. The system analyzes the trends in historical data to predict the possible oral health problems that users may face in the future, and evaluates the likelihood of each disease occurrence according to the disease occurrence probability model. Through risk assessment based on data analysis, the system can predict oral health problems in advance and help users take early intervention measures to prevent the occurrence of diseases or control the development of the condition.

[0031] The health management advice module includes an oral care advice unit, a diet advice unit, and a lifestyle adjustment unit. The oral care advice unit is used to provide users with personalized oral care plans through intelligent diagnosis results. The oral care plan includes brushing techniques, dental floss use, and mouthwash. The diet advice unit is used to provide diet guidance for oral health according to the user's eating habits. The diet guidance includes reducing sugar intake or increasing calcium-rich foods. The lifestyle adjustment unit is used to provide improvement suggestions on exercise and sleep based on the user's lifestyle data to promote oral health. The oral health management advice includes oral care methods, diet advice, and lifestyle adjustments.

[0032] Specifically, the oral care advice unit can identify the user's oral health problems, such as tooth decay, periodontal disease, tooth wear, etc., by analyzing the user's oral health conditions, especially through the disease identification and diagnosis results provided by the intelligent diagnosis module. According to these diagnosis results, corresponding oral care guidance will be provided for users, including recommending correct brushing techniques (such as brushing time, brushing method, brushing strength, etc.), dental floss use techniques and frequencies, mouthwash selection and use suggestions, etc. By combining with the user's intelligent devices (such as intelligent toothbrushes, intelligent oral monitoring devices, etc.), it realizes real-time monitoring and feedback of the user's oral care habits, and helps users establish and adhere to healthy oral care habits; The diet advice unit provides scientific diet guidance plans through the analysis of users' diet data. The system collects users' diet data through intelligent devices (such as smartphones, wearable devices, etc.), including the types of foods consumed daily, nutritional components, sugar and fat intake, etc. Combining with the users' oral health conditions, such as the risk of dental caries, gum health conditions, etc., personalized diet advice is automatically generated. By continuously monitoring the users' diet, the system will also adjust the diet advice according to the users' feedback and actual intake to ensure that the diet matches the oral health needs; The lifestyle adjustment unit provides personalized improvement suggestions based on users' lifestyle data. By obtaining data such as users' sleep time, sleep quality, exercise frequency and intensity through intelligent devices (such as mobile applications, wearable devices, etc.), and combining with users' oral health data, the system can analyze lifestyle problems that may affect oral health. The system will also adjust these suggestions according to the users' feedback data to make them more in line with the actual situation of users, thus effectively promoting oral health.

[0033] The real-time monitoring and feedback module includes a health data monitoring unit, an anomaly detection and alert unit, and a feedback and advice unit. The health data monitoring unit is used to monitor users' oral health data in real time and synchronize the data to the system cloud. Oral health data includes tooth cleanliness, gum bleeding conditions, etc. The anomaly detection and alert unit is used to automatically detect users' oral health anomalies and trigger alerts based on real-time monitoring data, reminding users to take corresponding measures. The feedback and advice unit is used to provide real-time feedback to users through mobile devices, enabling users to take intervention measures in a timely manner after discovering problems. Edge devices include smart watches, mobile phones, and bracelets.

[0034] Specifically, the health data monitoring unit is used to monitor users' oral health data in real time, such as tooth cleanliness, gum bleeding conditions, oral dryness, etc. By combining with intelligent devices (such as smart toothbrushes, oral sensor devices, etc.), the health data monitoring unit can collect users' oral health data and synchronize it to the system cloud in real time. After cloud processing, the system can provide a long-term trend analysis of users' oral health conditions to help users better manage their oral health.

[0035] The anomaly detection and alert unit is responsible for automatically detecting users' oral health anomalies and triggering alerts based on real-time monitoring data. When the system identifies abnormal situations, such as excessive gum bleeding, insufficient tooth cleanliness, etc., the anomaly detection and alert unit will immediately notify the user and generate an alert. The alert can be sent to the user through mobile devices (such as smart watches, mobile phones or bracelets) to remind them to take corresponding intervention measures, such as adjusting oral care habits or seeking professional treatment.

[0036] The Feedback and Suggestion Unit provides real-time feedback and personalized suggestions to users through mobile devices. When the system detects abnormal oral health data of users, the Feedback and Suggestion Unit not only issues an alarm but also provides specific action suggestions according to the abnormal situation. For example, if gum bleeding is detected, the system may suggest that the user change the brushing method, use a special toothpaste, increase the use of dental floss, etc. Users can receive real-time feedback through mobile devices and then intervene according to the suggestions, so as to effectively help users monitor their oral health, identify potential problems in a timely manner, and provide intervention measures at the initial stage of the problem during the use process through comprehensive health data monitoring, abnormal detection, and instant feedback. With the real-time monitoring and feedback of smart devices, users can take timely measures, thereby improving the efficiency of oral health maintenance and reducing the risk of oral diseases.

[0037] The Personalized Recommendation Module includes a Health Management Plan Generation Unit, a Lifestyle Suggestion Unit, and an Oral Care Reminder Unit. The Health Management Plan Generation Unit generates a personalized oral health management plan based on the health assessment results. The Lifestyle Suggestion Unit provides lifestyle suggestions for improving oral health according to the user's health status. The Oral Care Reminder Unit provides regular oral care reminders according to the user's health status.

[0038] Specifically, the Health Management Plan Generation Unit generates a personalized oral health management plan based on the user's health assessment results. The user's health assessment results include oral examination data, lifestyle data, historical health data, and diagnostic information provided by the Intelligent Diagnosis Module. The Health Management Plan Generation Unit combines these data to generate a specific management plan, such as oral care steps (including brushing frequency, dental floss use, mouthwash recommendation, etc.), diet adjustment suggestions, lifestyle improvement, etc., to meet the personalized needs of different users and regularly adjust the management plan according to the changes of users; The Lifestyle Suggestion Unit provides lifestyle suggestions for improving oral health according to the user's health status. By analyzing the user's lifestyle data such as eating habits, exercise volume, and sleep quality, the system can provide personalized suggestions for the user. The system may suggest that the user increase foods rich in calcium and vitamin C, reduce sugar intake, or increase exercise volume to improve oral health. The system will also suggest that they adjust their work and rest according to the user's lifestyle to ensure good sleep habits, thereby effectively preventing oral problems; The Oral Care Reminder Unit provides regular oral care reminders according to the user's health status. Based on the user's oral health data, intelligent diagnosis, and health assessment results, the Oral Care Reminder Unit will send regular reminders to the user to remind them to perform oral care tasks, such as brushing teeth correctly, using dental floss, mouthwash, etc. The frequency and content of the reminders will be adjusted according to the user's personalized needs to ensure that the reminder content is consistent with the user's oral health status.

[0039] The intelligent prediction module includes a prediction model training unit, a health trend prediction unit, and a personalized prediction adjustment unit. The prediction model training unit is used to train an oral health prediction model based on historical health data. The health trend prediction unit is used to predict the trend of the user's future oral health status according to the prediction model. The personalized prediction adjustment unit adjusts the prediction result according to the user's specific data.

[0040] Specifically, the prediction model training unit analyzes a large amount of historical health data and uses machine learning algorithms to train the oral health prediction model. The historical health data includes the user's oral examination records, lifestyle data, diagnosis information, and related health indicators. The dataset used by the prediction model training unit has been preprocessed and feature extracted, and can identify key factors affecting oral health, such as eating habits, genetic information, lifestyle, etc. Through model training, the system can extract important features affecting oral health, establish a regular model of oral health changes, and provide a basis for future health predictions; Based on the trained oral health prediction model, the health trend prediction unit combines the current user's real-time health data to predict the trend of the user's oral health status in the future for a period of time. The health trend prediction unit can analyze the user's existing health status and historical data, taking into account lifestyle, diet changes, and other health influencing factors, and generate a preliminary judgment result on the trend of oral health changes. The predicted content may include the future change trends of the occurrence probability of oral diseases (such as dental caries, periodontal disease, etc.), tooth wear degree, gum health, etc., to help users take preventive measures in advance; The personalized prediction adjustment unit adjusts the health trend prediction result according to the user's specific data to make it more personalized and accurate. The personalized prediction adjustment unit can fine-tune the original prediction result according to factors such as the user's actual health status, lifestyle, and family health history. By taking into account the user's personal special circumstances, such as drug use, treatment history, or recent health changes, the personalized prediction adjustment unit can more accurately predict the future trend of the user's oral health and provide more personalized health advice and intervention measures.

[0041] The remote diagnosis and treatment module includes a video diagnosis and treatment unit, a remote diagnosis unit, and a prescription management unit. The video diagnosis and treatment unit is used to provide remote diagnosis and treatment services through video conferencing. The remote diagnosis unit is used to conduct remote diagnosis through the collected data and images. The prescription management unit is used to issue oral health-related prescriptions according to the diagnosis results and manage electronic prescriptions.

[0042] Specifically, through video conferencing technology, the video diagnosis and treatment unit enables users to conduct real-time remote face-to-face diagnosis and treatment with dentists. Users can access the platform through intelligent devices (such as smartphones, tablets or computers), start the video diagnosis and treatment system, and have a video call with the doctor. The doctor can observe the user's oral condition through the video and ask about symptoms, medical history and other information. Remote consultation not only saves the user's time and energy, but also enables the user to obtain professional oral health advice and diagnosis guidance when they are unable to visit the clinic in person. The video diagnosis and treatment unit also supports real-time oral examinations in specific situations. The user provides image information (such as images or videos taken by oral imaging devices) through the electronic device to help the doctor make a better diagnosis; The remote diagnosis unit is used to conduct diagnostic analysis on the data and imaging materials submitted by the user through automated or semi-automated means on the basis of video diagnosis and treatment. Through the integrated data acquisition system, the user's oral health data (such as medical images, health records, diagnostic data, etc.) will be uploaded to the cloud platform or the diagnosis and treatment system. The remote diagnosis unit uses machine learning algorithms and deep learning models to analyze this data, and combines the doctor's remote observation results to conduct diagnosis and health problem assessment. The remote diagnosis unit can identify various oral health problems, such as dental caries, periodontal disease, tooth wear, etc., and feedback the diagnosis results to the doctor as the basis for further treatment; The prescription management unit issues oral-related prescriptions for users according to the remote diagnosis results and conducts electronic prescription management. The prescription management unit uses the built-in prescription generation tool in the system to automatically generate prescriptions that meet the needs of oral health treatment according to the doctor's diagnosis and advice. All prescription information will be stored in electronic form and the user's privacy will be protected through security encryption means. The electronic prescription can be directly sent to the pharmacy or the drug supplier designated by the user, and the user can pick up the drugs through the online platform or directly go to the designated location. The system can also monitor the usage of prescriptions in real time and make adjustments when necessary.

[0043] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made in these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An oral health management system based on big data, characterized in that: include: Data acquisition module, data fusion module, oral examination module, intelligent diagnosis module, health management suggestion module, real-time monitoring and feedback module, personalized recommendation module, intelligent prediction module and remote diagnosis and treatment module; The data collection module is used to collect various data related to the oral cavity from the collection device; The data fusion module is used to integrate and process multimodal data from different sources; The oral inspection module is used to inspect the inner wall of the oral cavity and the teeth and collect the inspection result data; The intelligent diagnosis module is used to identify oral health problems and diagnose oral diseases through deep learning and artificial intelligence algorithms; The health management suggestion module is used to provide users with personalized oral health management suggestions based on the intelligent diagnosis results; The real-time monitoring and feedback module is used to track the user's oral health status in real time and provide timely feedback and suggestions to the user through the edge device; The personalized recommendation module is used to provide users with personalized health management plans based on health assessment results and prediction data; The intelligent prediction module is used to predict the user's future oral health trends based on historical health data; The remote diagnosis and treatment module is used to provide auxiliary services for remote dental diagnosis and treatment.

2. The oral health management system based on big data according to claim 1, characterized in that: The data acquisition module includes an oral health data acquisition unit, a lifestyle data acquisition unit and a medical imaging data acquisition unit. The oral health data acquisition unit is used to collect data on tooth surface cleanliness, tooth wear and gum health through a smart toothbrush and oral sensor equipment. The lifestyle data acquisition unit is used to collect the user's diet, exercise and sleep lifestyle habit data through the user's smart device. The smart device includes a mobile phone application or a wearable device. The medical imaging data acquisition unit is used to collect the user's oral imaging data through an oral imaging device. The various oral data include oral health data, lifestyle habit data and medical imaging data.

3. The oral health management system based on big data according to claim 1, characterized in that: The data fusion module includes a data cleaning unit, a multimodal data fusion unit and a data analysis unit. The data cleaning unit is used to denoise, fill in missing values ​​and format various types of collected data. The multimodal data fusion unit is used to fuse multimodal information from different sensors, images and behavioral data to generate a complete oral health data model. The data analysis unit is used to analyze the fused data and identify potential oral health problems. The integration and processing include data cleaning, denoising and formatting.

4. The oral health management system based on big data according to claim 1, characterized in that: The oral detection module includes a caries detection unit, a periodontal disease detection unit, and a tooth wear detection unit. The caries detection unit is used to detect tooth caries, the periodontal disease detection unit is used to detect the health status of periodontal tissues, and the tooth wear detection unit is used to detect the degree of tooth wear.

5. The oral health management system based on big data according to claim 1, characterized in that: The intelligent diagnosis module includes a disease identification unit, a personalized diagnosis unit and a risk assessment unit. The disease identification unit automatically identifies oral diseases by performing deep learning analysis on the collected oral image data and health data. The personalized diagnosis unit is used to provide each user with personalized oral health diagnosis and suggestions based on the user's oral health status and living habits. The risk assessment unit is used to assess the user's oral health risk based on the user's health record, combined with historical data and a disease occurrence probability model. The oral diseases include caries and periodontitis.

6. The oral health management system based on big data according to claim 1, characterized in that: The health management suggestion module includes an oral care suggestion unit, a dietary suggestion unit and a lifestyle adjustment unit. The oral care suggestion unit is used to provide the user with a personalized oral care plan through intelligent diagnosis results. The oral care plan includes brushing techniques, flossing, and mouthwash. The dietary suggestion unit is used to provide dietary guidance that is beneficial to oral health based on the user's dietary habits. The dietary guidance includes reducing sugar intake or increasing calcium-rich foods. The lifestyle adjustment unit is used to provide improvement suggestions on exercise and sleep based on the user's lifestyle habit data to promote oral health. The oral health management suggestions include oral care methods, dietary suggestions and lifestyle adjustments.

7. The oral health management system based on big data according to claim 1, characterized in that: The real-time monitoring and feedback module includes a health data monitoring unit, an abnormality detection and alarm unit, and a feedback and suggestion unit. The health data monitoring unit is used to monitor the user's oral health data in real time and synchronize the data to the system cloud. The oral health data includes tooth cleanliness and gum bleeding. The abnormality detection and alarm unit is used to automatically detect user oral health abnormalities and trigger an alarm based on real-time monitoring data, reminding the user to take corresponding measures. The feedback and suggestion unit is used to provide real-time feedback to the user through a mobile device, so that the user can take timely intervention measures after discovering a problem. The edge devices include smart watches, mobile phones, and bracelets.

8. The oral health management system based on big data according to claim 1, characterized in that: The personalized recommendation module includes a health management program generation unit, a lifestyle recommendation unit and an oral care reminder unit. The health management program generation unit generates a personalized oral health management program based on the health assessment results, the lifestyle recommendation unit provides lifestyle recommendations for improving oral health based on the user's health status, and the oral care reminder unit provides regular oral care reminders based on the user's health status.

9. The oral health management system based on big data according to claim 1, characterized in that: The intelligent prediction module includes a prediction model training unit, a health trend prediction unit, and a personalized prediction adjustment unit. The prediction model training unit is used to train an oral health prediction model based on historical health data; the health trend prediction unit is used to predict the trend of the user's future oral health status according to the prediction model; and the personalized prediction adjustment unit adjusts the prediction results according to the user's specific data.

10. The oral health management system based on big data according to claim 1, characterized in that: The remote diagnosis and treatment module includes a video diagnosis and treatment unit, a remote diagnosis unit and a prescription management unit. The video diagnosis and treatment unit is used to provide remote diagnosis and treatment services through video conferencing, the remote diagnosis unit is used to perform remote diagnosis through collected data and images, and the prescription management unit is used to issue oral health-related prescriptions based on the diagnosis results and perform electronic prescription management.

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