Oral hypofunction self-detection method and system for old people

Abstract

The invention discloses a self-detection method and system for oral hypofunction of old people, and particularly relates to the technical field of medical health, the system comprises a login unit, an evaluation questionnaire unit and an intervention guidance unit, and the method comprises the following steps: B1, user registration and login; b2, performing dynamic logic interactive evaluation; b3, performing multi-dimensional classification evaluation; b4, risk grading and intervention generation; by means of the system and method, the elderly can complete self-detection at home through a mobile phone applet, self-detection can be conducted on the oral cavity weakness progress of the elderly anytime and anywhere, an oral cavity health exercise method can be provided according to problems, the oral cavity weakness progress of the elderly is delayed, and the life quality of the elderly is improved; software adopts audio-video combination, image-text combination and other modes, the oral health condition of an evaluator is obtained through questions and answers, the answers are based on selection questions, subjective assume or ambiguity is avoided, and the self-detection success rate and accuracy of old people are improved.

Description

Technical Field

[0001] The present invention relates to the field of medical and health technologies, and more specifically, to a self-detection method and system for the decline of oral functions in the elderly. Background Art

[0002] Oral health is a key part of maintaining overall health. As time goes by, our oral functions will decline to varying degrees, which not only affects our daily diet but may also trigger a series of changes in physical health conditions and social barriers. In order to delay this process and prevent oral diseases caused thereby, it can be achieved through a series of scientific oral frailty examinations and effective coping strategies. Considering that some testers may have inconvenient mobility and there are situations such as high costs and complex detections when going to the hospital for detections, these oral frailty detection functions can be integrated into mobile mini-programs or applications so that they can conduct self-detections anytime and anywhere, thereby improving the popularity and convenience of oral frailty detections. Such an innovation can not only improve the quality of life of individuals but also actively advocate for a healthy lifestyle;

[0003] At present, the medical service facilities for oral health care in China are not yet perfect. Community hospitals are unable to carry out examinations on the oral functions of the elderly, which is not conducive to the early identification and intervention of oral frailty in the elderly. Oral hospitals and other medical institutions can provide diagnostic information for oral diseases, but they cannot provide a convenient and effective solution for the functional problem of oral frailty. Moreover, the improvement of oral frailty requires the cooperation of multiple disciplines such as oral physicians, dietitians, and rehabilitation therapists. The single outpatient diagnosis and treatment in oral hospitals cannot solve the problem of oral frailty. In addition, the self-care ability of the elderly weakens, and going to the hospital for medical treatment increases the burden on the family support system, with repeated medical treatments and increased economic expenditures.

[0004] Therefore, a self-detection method and system for the decline of oral functions in the elderly are proposed to address the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a self-detection method and system for the decline of oral functions in the elderly to solve the problems raised in the above background art.

[0006] To achieve the above object, the present invention provides the following technical solution: A self-detection system for the decline of oral functions in the elderly, including a login unit, an assessment questionnaire unit, and an intervention guidance unit,

[0007] The login unit: used for user registration and login, including a mobile phone number verification module, a basic information entry module, and a historical data management module;

[0008] The assessment questionnaire unit: used for comprehensively evaluating the oral health status of the elderly, specifically including:

[0009] Dynamic logic jump module: Automatically adjust the subsequent question path according to the user's answer;

[0010] Multimodal interaction module: Display self-check questions in a combination of pictures and texts;

[0011] Classification and evaluation module: Evaluate the user's oral function from the dimensions of denture adaptability, saliva evaluation, oral coordination, oral health awareness, user diet rationality, and user motor ability through a question chain;

[0012] The intervention guidance unit: Used to generate personalized health advice according to the evaluation results, classify the oral frailty risk into four categories according to the evaluation results: severe risk, moderate risk, mild risk, and no risk, and generate health guidance plans in text and voice forms for different risk levels.

[0013] Preferably, the mobile phone number verification module sends a verification code through the SMS service. After the user enters the verification code, the system verifies its correctness to complete the identity authentication; the basic information entry module performs a legality check on the gender, date of birth, height, and weight information entered by the user during registration; the historical data management module loads the user's historical test records from the database after the user logs in, displays them in reverse chronological order, the user can click on a certain record to view the detailed results, and can modify the registration information.

[0014] Preferably, the operation steps of the dynamic logic jump module are as follows:

[0015] S1. Let the question set be Q = {Q1, Q2,..., Q n}, where Q i represents a question;

[0016] S2. The jump rule of the question is:

[0017] Q i ·next question rules = {(option1: Q j ), (option2: Q k ),...};

[0018] After the user selects option x , the next Q i is:

[0019] next question id = Q i ·next question rules[option x ;

[0020] Among them, Q i· The "next question rules" represent the defined jump paths for the next question after the user selects different options; the "next question id" represents the ID of the next question calculated based on the user's selection, driving the dynamic adjustment of the evaluation process; "options" represents the option list. The next question is loaded according to the "next_question_id". If the "next_question_id" is empty, the evaluation ends. Through the above formula, when the user selects an option in question Q i in the option x , the system determines the ID of the next question Q j by looking up the jump rule table.

[0021] Preferably, the multimodal interaction module further includes a voice Q&A function and graphic and text auxiliary explanations. After the multimodal interaction module collects the user's voice input in real time through the device microphone, it calls the voice Q&A function to convert the voice stream into text. Then, the multimodal interaction module performs keyword matching on the recognized text with the preset answers to activate the graphic and text auxiliary explanations. The multimodal interaction module loads graphic and text resources from the local cache according to the question ID and embeds them in the specified area of the interface for display.

[0022] Preferably, the question chain of the classification and evaluation module designs questions based on the health behavior model and the health risk assessment theory, and the questions are designed following a hierarchical structure from general to specific. The health behavior model evaluates the user's oral health care awareness and behavior habits, and the health risk assessment theory collects data from the user's teeth, saliva, and coordination dimensions to quantify the user's oral frailty risk.

[0023] Preferably, the classification and evaluation module analyzes the original data submitted by the user through the evaluation questionnaire unit, and the analysis steps are as follows:

[0024] A1. Perform text conversion and semantic parsing on unstructured data, perform standardized encoding on structured data, and at the same time, if the user does not answer the required questions, the classification and evaluation module triggers an automatic reminder;

[0025] A2. Extract key features from the preprocessed data according to the preset evaluation dimensions and assign weights to each feature;

[0026] A3. Calculate the score of each dimension according to the feature values and weights, and apply classification rules to determine the final risk level. The calculation formula for the final risk level is:

[0027]

[0028] where, Total Score represents the final risk level; Feature iRepresents a feature; Weight i Represents the weight, and divides the risk level according to the calculated total range:

[0029] Severe risk: Total score ≤ 40;

[0030] Moderate risk: 40 < Total score ≤ 60;

[0031] Mild risk: 60 < Total score ≤ 80;

[0032] No risk: Total score > 80;

[0033] A4. Cross-validate the key dimensions to avoid deviation of a single indicator. At the same time, match the classification result with the intervention plan library to generate personalized suggestions.

[0034] A self-detection method for the decline of oral function in the elderly, including the following steps:

[0035] B1. User registration and login: Enter the user's mobile phone number through the mobile terminal and send a verification code to complete identity authentication. Collect the user's basic information, including gender, date of birth, height and weight, and perform legality verification. Store the user information and historical detection records, and support viewing and modification after login;

[0036] B2. Dynamic logic interactive evaluation: Display questions in a combination of voice playback and graphics and text. The user answers by checking options or voice input;

[0037] B3. Multi-dimensional classification evaluation: The user quantifies the current status of oral function by answering question chains and uploads it to the self-detection system for semantic analysis;

[0038] B4. Risk grading and intervention generation: Divide the risk of oral function decline into four levels: severe, moderate, mild and no risk according to the evaluation results, and generate personalized health suggestions for different levels;

[0039] B5. Data synchronization and remote docking: The user's detection data is uploaded to the cloud, and multi-device synchronous access is supported.

[0040] Preferably, the multi-dimensional classification evaluation specifically evaluates the current status of the user's oral function from five dimensions, and the five dimensions are: oral health status, oral coordination, oral health care awareness, diet rationality and motor ability.

[0041] The technical effects and advantages of the present invention:

[0042] 1. Compared with the prior art, this self - detection method and system for the decline of oral function in the elderly realizes home self - detection through a mobile application or mini - program. Users can complete the oral frailty assessment without going to the hospital, saving time and transportation costs. It is especially suitable for the elderly with limited mobility. At the same time, it can be detected anytime and anywhere, improving the popularity and convenience of detection.

[0043] 2. Compared with the prior art, this self - detection method and system for the decline of oral function in the elderly uses standardized multiple - choice questions and quantitative tests to avoid subjective assumptions or ambiguous answers. Through objective data quantification for evaluation, it reduces human errors, and adopts dynamic logical jumps to ensure the personalization of the question path, avoiding redundant questions from interfering with the results.

[0044] 3. Compared with the prior art, this self - detection method and system for the decline of oral function in the elderly combines voice playback, graphic and text explanations, and video teaching to lower the operation threshold for the elderly. The voice - based Q&A function is adapted to users with reduced vision or hearing, and the graphic and text auxiliary explanations enhance the information transmission effect.

[0045] 4. Compared with the prior art, this self - detection method and system for the decline of oral function in the elderly comprehensively evaluates oral function from six dimensions: teeth, saliva, oral coordination, health awareness, diet, and exercise, covering multiple key areas of oral health. The evaluation results are more comprehensive, and accurate classification is achieved through quantitative indicators.

[0046] 5. Compared with the prior art, this self - detection method and system for the decline of oral function in the elderly enhances the self - health care awareness of the elderly through health advice and educational content, corrects the cognitive misunderstandings of the elderly, and enhances their health management ability. Through regular re - testing and intervention suggestions, it delays the progress of oral frailty. At the same time, it reduces the number of times the elderly go to the hospital, reduces medical expenses and the burden on family support, and reduces the occupation of medical resources through home detection and remote intervention. Description of the Drawings

[0047] Figure 1 It is a block diagram of the system of the present invention.

[0048] Figure 2 It is a flowchart of a self - detection method for the decline of oral function in the elderly of the present invention.

[0049] Figure 3 It is a schematic diagram of the interface effect of the mini - program of the present invention.

[0050] Figure 4 It is a schematic diagram of the interface effect of the missing tooth selection program of the present invention.

[0051] Figure 5 It is a schematic diagram of the display effect of the evaluation results of the present invention. Detailed Embodiments

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] Embodiment 1

[0054] As shown in the attached Figures 1 to 5 An elderly oral function decline self-detection system, including a login unit, an assessment questionnaire unit, and an intervention guidance unit.

[0055] Login unit: The user obtains a text message verification code by entering a mobile phone number, and the system completes the verification through a third-party text message platform to ensure the authenticity of the identity. Form controls such as a date picker and a number input box are used to collect the user's gender, date of birth, height, and weight data, and the input legality is verified in real time. At the same time, after the user logs in, the system loads its historical detection records from a database such as MySQL, supports viewing and information modification sorted by time, and the modified data ensures atomic update through a transaction mechanism.

[0056] Assessment questionnaire unit: used to comprehensively evaluate the oral health status of the elderly, specifically including:

[0057] Dynamic logic jump module: Based on a preset rule engine such as Drools, the problem path is dynamically adjusted. For example:

[0058] When the user selects "no dentures", the system automatically skips sub-questions related to denture adaptability, such as wearing duration and cleaning frequency, and the problem path length is shortened by 40%.

[0059] When the abnormal salivary secretion volume is <1.2 ml / 10 min, it is forced to jump to the dry mouth intervention advice interface; the problem path is intelligently adjusted through the rule engine, reducing redundant questions by 30% - 50%, and the detection time is shortened from 20 minutes of the traditional questionnaire to within 10 minutes. Logic jump rules such as "no dentures → skip 7 sub-questions" avoid interference from invalid data and improve the reliability of the evaluation results.

[0060] Multi-modal interaction module: The questions are presented in combination with pictures and texts. For example, tooth-related questions are embedded with tooth number diagrams, and the user can mark the missing tooth positions by clicking. The voice question-and-answer function integrates a voice recognition API such as Baidu Voice Recognition, supports the user to input answers by voice, the system converts them into text in real time and matches the options. The voice question-and-answer function reduces the operation threshold for the elderly, and the voice recognition accuracy rate is above 90%. The combination of pictures and texts such as teaching videos and marked diagrams improves the information transmission efficiency, and the user understanding degree is increased by 40%.

[0061] Classification evaluation module: Evaluate from the following perspectives through a question chain:

[0062] Denture adaptability: Quantify the adaptability score through a question chain such as denture type, wearing duration, and looseness;

[0063] Saliva evaluation: Standardize the "10-minute spitting method" to guide users to collect saliva volume. After input, the system matches the preset threshold. For example, <1.2 ml / 10 min is abnormal;

[0064] Oral coordination: The user pronounces continuously and quickly, such as "pada ka". The system evaluates the pronunciation clarity and the number of completed groups through audio analysis technology;

[0065] Oral health awareness: Quantify the level of health awareness through questions such as brushing frequency and floss use;

[0066] User diet rationality and user motor ability: Quantify indicators such as vegetable intake, such as "whether it reaches 500 g / day", and exercise duration "≥150 minutes per week";

[0067] Intervention guidance unit: Used to generate personalized health suggestions based on the evaluation results. Divide the risks into four levels according to the weighted total score (for example, the tooth dimension accounts for 30%, and saliva accounts for 20%):

[0068] Severe risk (≤40 points): Prompt to seek medical attention immediately;

[0069] Moderate risk (41 - 60 points): Recommend retesting and lifestyle intervention;

[0070] Mild risk (61 - 80 points): Provide daily health care suggestions;

[0071] No risk (>80 points): Feedback that the oral function is normal. Then, for denture users, provide the cleaning steps of "brush - soak - brush again" and a reminder to disable bleach. At the same time, generate text + voice dual-modal suggestions for high-risk users, such as "drink 2000 ml of water daily and retest regularly", and adapt to groups with visual or hearing impairments.

[0072] Furthermore, the complete process from evaluation to intervention covers six dimensions, with a super-high accuracy rate for risk classification. The personalized suggestion generation engine supports dynamic matching of more than 500 health knowledge items, and the adoption rate of the intervention plan is improved.

[0073] Based on Example 1, the solution in Example 1 is further refined and introduced in combination with the following specific working methods, such as Figures 1 to 5 As shown, see the following description for details:

[0074] As a preferred implementation, after the user enters the mobile phone number, the system calls a third-party SMS service such as Alibaba Cloud SMS service to send a 6-digit random verification code. The verification code is valid for 5 minutes. After the user enters the verification code, the system completes the identity authentication by comparing the entered verification code with the sent verification code. If the verification code is incorrect or times out, the system prompts the user to obtain a new verification code and limits the maximum number of verification codes sent per day to 5 times to prevent malicious brushing; the third-party SMS service is used to quickly send and verify the verification code, and the response time is less than 1 second to ensure a smooth user registration process. At the same time, the validity period of the verification code and the limit on the number of sent times effectively prevent malicious attacks;

[0075] Then when the user registers, they need to enter their gender (male / female), date of birth (selected through a date picker), height in centimeters with an input range of 50 - 250 cm, and weight in kilograms with an input range of 20 - 200 kg. The system validates the legality of the input data in real-time. For example:

[0076] The date of birth cannot be later than the current date;

[0077] The height and weight need to be within a reasonable range. If the range is exceeded, the user is prompted to re-enter;

[0078] After the data verification passes, the system stores the user information in a database such as MySQL and generates a unique user ID. The system validates the legality of the user input data in real-time to prevent invalid data such as negative height from entering the system, improving the data accuracy rate. Through the date picker and range limit controls, the user operation is simplified and the registration time is shortened;

[0079] After the user logs in, the system loads their historical test records from the database and displays them in reverse chronological order of the test time. After the user clicks on a certain test record, the system loads the detailed results of that test, such as scores for each dimension, risk level, and health advice. The user can modify their registration information such as height and weight. The system uses a transaction mechanism to ensure the atomicity and consistency of data updates. Displaying the historical test records in reverse chronological order allows the user to quickly locate the latest test results, improving the operation efficiency. Supporting the user to modify registration information such as height and weight ensures real-time data updates and improves user satisfaction.

[0080] As a preferred implementation, the core function of the dynamic logic jump module is to automatically adjust the path of subsequent questions based on the user's answers to the current question to achieve personalized assessment. The calculation steps are as follows:

[0081] S1. Let the question set be Q = {Q1, Q2,..., Q n}, where Q i represents a question;

[0082] S2. The jump rule for questions is:

[0083] Q i · Next question rules = {(option1: Q j ), (option2: Q k ),...};

[0084] After the user selects an option x the next Q i is:

[0085] next question id = Q i · next question rules[option x ;

[0086] Among them, Q i · next question rules represents the jump path of the next question after the user selects different options; next question id represents the ID of the next question calculated based on the user's selection, driving the dynamic adjustment of the evaluation process; options represents the option list, and the next question is loaded according to next_question_id. If next_question_id is empty, the evaluation ends. Through the formula, when the user selects option option i in question Q x , the system determines the ID of the next question Q j by looking up the jump rule table. Further, each question (Question) is defined as an object with the following attributes:

[0087] next_question_id: The unique identifier of the question;

[0088] question_next: The question text;

[0089] options option list, such as [A: Yes; B: No];

[0090] Q i · nextquestionrules: Jump rule, in the format of {option: next question ID};

[0091] After the user selects an option, the system parses the selection and matches the jump rule.

[0092] As a preferred implementation, the multimodal interaction module further includes a voice Q&A function and graphic and text auxiliary explanations. After the user clicks the "Voice Answer" button, the system collects voice input in real time through the device microphone, performs noise reduction processing, and calls a voice recognition API (such as Baidu Voice Recognition) to convert the voice stream into text. The system performs keyword matching on the recognized text with preset answer options. For example:

[0093] When the user answers "I brush my teeth every day", it matches the option "A: Basically yes";

[0094] If the matching fails, the system prompts the user to retry or manually select an answer. The voice input function reduces the typing operation difficulty for the elderly, and the user operation time is shortened;

[0095] The system loads graphic and text resources such as picture URLs and video IDs from the local cache or the server according to the question ID and embeds them in the specified area of the interface for display. In tooth-related questions, a tooth number diagram is embedded. The user can mark by clicking on the missing tooth position. In brushing-related questions, a teaching video of the "Bass Brushing Method" is embedded. The user can watch by clicking the play button. If the user modifies the answer, such as reselecting the missing tooth position, the graphic and text content is updated in real time according to the new answer. The combination of graphics and text to display questions such as tooth number diagrams and teaching videos improves the user's understanding. The dynamic update function ensures that the graphic and text content is synchronized with the user's answer in real time, and the information transmission efficiency is improved. Further, through the two core innovations of voice Q&A and graphic and text assistance, this multimodal interaction module solves the pain points of complex traditional questionnaire operations and unintuitive information transmission, providing users with a convenient, intuitive, and efficient operation experience.

[0096] As a preferred implementation, the question chain of the classification and evaluation module designs questions based on the health behavior model and the health risk assessment theory, and the questions are designed following a hierarchical structure from general to specific. The health behavior model evaluates the user's oral health care awareness and behavior habits, and the health risk assessment theory collects data from the user's tooth, saliva, and coordination dimensions to quantify the user's oral frailty risk. Specifically, the assessment of the oral health status of the elderly is completed in the form of audio-visual combination questions and tick-box answers. The title bar displays oral-related parts, such as teeth, gums, saliva, mucous membranes, etc. The user clicks the speaker icon after clicking on the "Specific Test Questions" to enter the voice Q&A session. After carefully listening to or reading the specific oral questions, the user can tick the corresponding answer options. After ticking is completed, click the "Next" button to continue answering the next oral question.

[0097] 1. The tooth-related questions are as follows:

[0098] Click on the missing tooth number;

[0099] Do you have dentures;

[0100] Can you remove your dentures at will?

[0101] Daily wearing time of dentures;

[0102] Will the dentures become loose or even fall out in the mouth when speaking or eating?

[0103] Do you feel pain or pressure discomfort when wearing dentures?

[0104] Can you eat as freely as your natural teeth after wearing dentures?

[0105] Can food residues always be seen on the teeth?

[0106] Are you satisfied with the appearance of your dentures?

[0107] Are there obvious holes in your teeth?

[0108] Do your teeth ache in response to stimuli such as acid, sweet, cold wind, etc.?

[0109] Do your teeth suddenly ache during sleep or other times?

[0110] Do you feel that your teeth have become longer than when you were young?

[0111] 2. Questions about saliva are as follows:

[0112] You need to cooperate to complete the following test to obtain the saliva secretion volume in your oral cavity, also known as the "static total saliva flow rate", which can reflect the basal secretion volume of your salivary glands under no stimulation. We can use the spitting method. Prepare a clean and dry small cup. Before starting the test, swallow all the saliva in your mouth. Click the countdown for 10 minutes to start collecting all the saliva produced in your mouth. During this stage, try to make the saliva gather at the bottom of the mouth. The subject spits it into a test tube every 60s and collects it for 10 minutes. Less than 1ml / 10min is abnormally reduced. After the test, how many milliliters of saliva did you spit out in 10 minutes? The answer options (single choice) are as follows:

[0113] A: Less than 1.2ml / 10min, indicating impaired saliva secretion or dry mouth

[0114] B: Less than 6ml / 10min, indicating possible dry mouth

[0115] C: More than 6ml, indicating no dry mouth

[0116] 3. Questions about mucosa are as follows:

[0117] Do you often have oral ulcers in your oral cavity?

[0118] 4. Oral coordination test is as follows:

[0119] Take a deep breath and then quickly and continuously utter "pa", "da", "ka", "pa da ka" in one breath as one set. See how many sets can be said in one breath. Note that the voice cannot be too soft, and the pronunciation of each word should be as clear as possible, and each syllable must be complete; whether the pronunciation was clear in the previous oral coordination test and 3 sets or more of the test were completed;

[0120] 5. Health awareness questions are as follows:

[0121] Please select your frequency of oral health examinations or medical consultations in the past year;

[0122] 6. Brushing teeth questions are as follows:

[0123] Do you brush your teeth as shown in the diagram? At the same time, embed a video of the Bass method of brushing teeth below the question;

[0124] Do you brush your teeth at least once after dinner and before going to bed?

[0125] Do you use auxiliary tools such as dental floss and interdental brushes?

[0126] 7. Food balance questions are as follows:

[0127] Does the total amount of vegetables consumed per day reach one catty?

[0128] Does the amount of meat consumed per day reach about two liang?

[0129] Can the number of eggs consumed per day reach 1?

[0130] Can the daily intake of dairy products reach 250 ml?

[0131] Can the amount of water drunk per day reach 1000 ml?

[0132] 8. Diet preference questions are as follows:

[0133] The high-sugar diet consumed every day includes;

[0134] Highly acidic foods consumed daily;

[0135] 9. Exercise questions are as follows:

[0136] Do you exercise on weekdays?

[0137] The exercise items on weekdays include;

[0138] The daily exercise duration;

[0139] The weekly exercise frequency;

[0140] The sweating situation during exercise;

[0141] The physical fatigue and heart rate increase after exercise;

[0142] Has there been a fall in the past year?

[0143] After the user completes all the test questions, an interface will be presented so that the user can clearly understand their oral risk status. At the same time, for the question "Click on the missing tooth number", click on a number, which represents the loss of 1 tooth. The corresponding health education is as follows:

[0144] Adults should have 28 permanent teeth, also called natural teeth, which are symmetrically arranged top and bottom, forming a good occlusion, facilitating good occlusion and chewing during eating. If too many teeth are missing, especially if the corresponding teeth on the upper and lower jaws are both missing, the ability to occlude top and bottom will be lost. For chewing harder foods such as poultry and other meats, nuts such as peanuts and soybeans, and fiber-rich vegetables such as radishes and celery, it will cause a certain degree of difficulty in ingestion. In the long term, it will inevitably lead to nutritional deficiencies. Multiple studies have confirmed that compared with respondents with 0-8 missing teeth, the risk of limited activities of daily living increases for those with 9-27 and 28 missing teeth. Therefore, the elderly must take good care of their teeth, cherish every tooth of their own, and treat dental caries and periodontitis as early as possible. If dental caries and periodontitis can no longer be repaired, in order to avoid causing more dental health problems, measures such as tooth extraction are also required. Here, it is necessary to tell the elderly that we are not afraid of tooth loss. The key is that the teeth should be healthy. If there is a tooth loss, it is necessary to go to a regular hospital for examination as soon as possible. Under the condition that the physical condition permits, fill the tooth position by means of denture insertion, dental implantation, etc.

[0145] Regarding the relevant knowledge of dentures, the corresponding health education is as follows:

[0146] Dentures are the general term for prostheses after tooth loss in the oral cavity. Dentures are also called "false teeth". False teeth can be understood as teeth that "fulfill their obligations" on behalf of the missing teeth for humans, that is, they replace the normal teeth to complete the chewing of food and maintain a good facial appearance.

[0147] Regarding whether dentures can be removed at any time, the corresponding health education is as follows:

[0148] Dentures are divided into three types: removable dentures, fixed dentures, and implant dentures. Removable dentures are false teeth that can be removed and worn by oneself, and are suitable for the situation of missing most teeth and having few remaining teeth. Fixed dentures are supported by the healthy teeth on both sides of the missing tooth and are fixed in the oral cavity, and cannot be removed by oneself. They are more comfortable to wear, but are only suitable for missing a few teeth. Implant dentures do not require the support of adjacent teeth, are more comfortable, but are more expensive.

[0149] Regarding the wearing and maintenance of removable dentures, the corresponding health education is as follows:

[0150] Removable partial dentures, also known as removable prostheses, are made by traditional paraffin casting methods. Now, with computer-aided design, different manufacturing processes may affect the comfort, strength, and aesthetics of denture wear. Dentures can be single, multiple, or even upper or lower rows and full dentures. Good fit of removable partial dentures can reduce plaque accumulation and also reduce the occurrence of complications such as tenderness. Therefore, it is very important to make a denture or a set of dentures that suit oneself. During the wearing process, the dentures should also be kept as clean as possible to protect the health of other teeth and reduce the occurrence of gingivitis, oral mucosal bacterial inflammation, etc.

[0151] It is generally recommended to remove the dentures thoroughly before going to bed every night and clean them at least once during the day. If conditions permit, the dentures can be removed and cleaned after each meal before wearing them again, especially after eating foods that are likely to adhere to the roots of the dentures.

[0152] The basic principles of cleaning dentures: brush, soak, and then brush again. Prepare a bowl of water. Brush the dentures first before soaking them to remove food residues. Use a foaming denture cleaner, which helps to remove stubborn stains and makes the dentures feel fresher. After soaking the dentures, brush them again, just like brushing real teeth. Note not to rub too hard to avoid leaving indentations on the surface of the dentures over time. It is recommended to use toothpaste and a small or medium-headed toothbrush to clean all surfaces of the dentures, including the surfaces that fit against the gums. But be careful not to use any bleaching products to clean the dentures because bleach will make the dentures less sturdy. Also, do not soak the dentures in very hot water, as this will also weaken the dentures and make them prone to breakage. Some partial dentures have soft liners, which can reduce gum sensitivity. There are also some dentures made of metal components or with clasps. In these cases, cleaning should be confirmed with the dentist and done gently to avoid damage.

[0153] Dentists often recommend removing the dentures at night to give the mouth a chance to rest. After cleaning the removed dentures, they should be placed in water to prevent cracking or deformation.

[0154] As a preferred implementation, the classification evaluation module analyzes the original data submitted by the user through the evaluation questionnaire unit. The analysis steps are as follows:

[0155] A1. Perform text conversion and semantic parsing on unstructured data, perform standardized coding on structured data, and at the same time, if the user fails to answer required questions, the classification evaluation module triggers an automatic reminder.

[0156] A2. Extract key features from the preprocessed data according to the preset evaluation dimensions and assign weights to each feature.

[0157] A3. Calculate the scores for each dimension based on the feature values and weights, and apply classification rules to determine the final risk level. The calculation formula for the final risk level is:

[0158]

[0159] Among them, Total Score represents the final risk level; Feature i represents a feature; Weight i represents the weight. The risk level is divided according to the calculated total range:

[0160] Severe risk: total score ≤ 40;

[0161] Moderate risk: 40 < total score ≤ 60;

[0162] Mild risk: 60 < total score ≤ 80;

[0163] No risk: total score > 80;

[0164] A4. Cross-validate the key dimensions to avoid the deviation of a single indicator. At the same time, match the classification result with the intervention plan library to generate personalized suggestions.

[0165] Example 2

[0166] As shown in the attached Figures 1 to 5 An elderly oral function decline self-detection method shown, according to an elderly oral function decline self-detection system, includes the following steps:

[0167] B1. User registration and login: The user inputs the mobile phone number through the mobile terminal and obtains the SMS verification code. The system calls the third-party SMS service such as Alibaba Cloud SMS service to complete the verification to ensure the authenticity of the identity, collects the user's basic information of gender, date of birth, height, and weight, and passes the legality verification such as the height range of 50 - 250 cm and the weight range of 20 - 200 kg. The user information and historical detection records are stored in the database such as MySQL, supporting viewing and modification after login. The modified data ensures atomic update through the transaction mechanism;

[0168] B2. Dynamic logic interactive evaluation: Display the questions in the way of voice playback combined with pictures and texts. The user answers by checking options or voice input. At the same time, automatically adjust the question path according to the user's answer, and realize the intelligent adjustment of the question path through the rule engine, reduce redundant questions, avoid the interference of invalid data, and improve the reliability of the evaluation result;

[0169] B3. Multi-dimensional classification evaluation:

[0170] The user answers through the question chain, and the system quantifies the current status of oral function and uploads it to the self-detection system for semantic analysis;

[0171] Tooth function evaluation: Quantify the number of missing teeth, denture adaptability, and caries situation through the question chain;

[0172] Salivary function assessment: Guide users to collect saliva volume through the "10-minute spitting and collection method", match the preset risk level, standardize the "10-minute spitting and collection method" to realize the first home self-test of salivary secretion volume, and the correlation with clinical test results reaches 0.85;

[0173] Oral coordination assessment: Assess the oral muscle function through continuous pronunciation tests such as "pada ka";

[0174] Healthcare awareness and behavior assessment: Quantify the level of health awareness through questions such as brushing frequency and floss use;

[0175] Diet and exercise assessment: Quantify indicators such as vegetable intake (e.g., "whether it reaches 500g / day") and exercise duration (e.g., "≥150 minutes per week"). The complete process from assessment to intervention covers six dimensions with a high risk classification accuracy rate.

[0176] B4. Risk grading and intervention generation: According to the assessment results, the risk of oral function decline is divided into four levels:

[0177] Severe risk (≤40 points): Prompt to seek medical attention immediately;

[0178] Moderate risk (41 - 60 points): Recommend retesting and lifestyle intervention;

[0179] Mild risk (61 - 80 points): Provide daily healthcare advice;

[0180] No risk (>80 points): Feedback that the oral function is normal.

[0181] Generate personalized health advice, such as:

[0182] For denture users, provide cleaning steps of "brush - soak - brush again" and a reminder to avoid using bleach;

[0183] Generate text + voice bimodal advice for high-risk users, such as "Drink 2000ml of water daily and retest regularly";

[0184] B5. Data synchronization and remote docking: Upload users' test data to the cloud, support multi-device synchronous access, connect to the medical institution system through the API interface, realize the integration of test results and medical records, and connect the test data to the hospital information system through the RESTful API to achieve seamless connection between "home self-test - hospital diagnosis and treatment", improving the utilization rate of medical resources.

[0185] Based on Example 2, the solution in Example 2 is further refined and introduced in combination with the following specific working methods, as Figures 1 to 5 shown, and the details are described below:

[0186] As a preferred embodiment, the multi-dimensional classification assessment specifically evaluates the current status of the user's oral functions from five dimensions, namely: oral health status, oral coordination, oral health awareness, dietary rationality, and exercise ability. Specifically, through a question chain, the number of missing teeth, denture adaptability such as wearing duration, looseness, and caries status are dynamically evaluated. The user clicks on the tooth number diagram to mark the missing tooth positions, and the system automatically records and quantifies the scores. For the saliva function test, the "10-minute spit and collection method" is used. The user collects the saliva volume according to the countdown prompt and inputs it, and the system matches the preset threshold. The user completes the test by continuously pronouncing quickly such as "pada ka", and the system evaluates the pronunciation clarity and the number of completed groups through audio analysis technology. If less than 3 groups are completed, it is determined as low coordination. The test results are synchronously sent to the risk grading engine in real time to trigger targeted intervention suggestions. The user's health awareness is evaluated through multiple-choice questions such as "Do you brush your teeth twice a day?" and embedded teaching videos such as the Bass brushing method. After the user answers, the system quantifies the cognitive level according to the preset rules. The user inputs the daily intake of vegetables, meat, and dairy products, and the system compares it with the recommended standards such as 500g of vegetables per day to generate a dietary deviation score. For high-sugar / high-acidic dietary preferences, the system prompts the risks through pictures and texts and recommends alternative solutions. The exercise type such as tai chi and walking, duration such as ≥30 minutes per time, and frequency are quantified through a question chain, and the exercise suitability is comprehensively evaluated in combination with the physical reactions after exercise such as heart rate changes and fatigue feelings.

[0187] For the oral health status assessment, the "tooth number diagram marking + saliva quantification test" is adopted, and the accuracy is higher than that of traditional questionnaires. For the oral health awareness assessment, teaching videos and multiple-choice questions are combined to improve the user's health awareness. At the same time, for the dietary rationality assessment, alternative solutions are generated through intelligent recommendation algorithms, and the adoption rate of the user's dietary improvement is increased.

[0188] The working process of the present invention is as follows: Enter the mobile phone number through the mobile terminal and obtain the SMS verification code. The system calls a third-party SMS service such as Alibaba Cloud SMS service to complete the verification to ensure the authenticity of the identity. The basic information of the user such as gender, date of birth, height, and weight is collected, and legal validity checks such as height range of 50 - 250 cm and weight range of 20 - 200 kg are carried out. The user information and historical detection records are stored in a database such as MySQL, which supports viewing and modification after login. The modified data ensures atomic update through a transaction mechanism.

[0189] Then, the questions are presented in a combination of voice playback and pictures and texts. The user answers by checking options or voice input. At the same time, the question path is automatically adjusted according to the user's answers. The intelligent adjustment of the question path is realized through a rule engine, reducing redundant questions, avoiding interference from invalid data, and improving the reliability of the evaluation results.

[0190] The user answers questions through a question chain. The system quantifies the current status of oral functions and uploads it to the self-detection system for semantic analysis. According to the evaluation results, the risk of oral function decline is divided into four levels and personalized health suggestions are generated. At the same time, the user's detection data is uploaded to the cloud to support multi-device synchronous access. Through the API interface, it is docked with the medical institution system to realize the integration of detection results and medical records. The detection data is docked with the hospital information system through the RESTful API to achieve seamless connection of "home self-detection - hospital diagnosis and treatment". The above is the working principle of the self-detection method and system for oral function decline in the elderly.

Claims

1. A self-detection system for oral function impairment in the elderly, comprising a login unit, an evaluation questionnaire unit and an intervention guidance unit, characterized in that: The login unit is used for user registration and login, including a mobile phone number verification module, a basic information entry module and a historical data management module; The assessment questionnaire unit is used to conduct a comprehensive assessment of the oral health status of the elderly, specifically including: Dynamic logic jump module: automatically adjust the path of subsequent questions according to user answers; Multimodal interaction module: displays self-check questions through a combination of pictures and texts; Classification assessment module: evaluates the user's oral function from the dimensions of denture fit, saliva assessment, oral coordination, oral health awareness, user diet rationality and user motor ability through a chain of questions; The intervention guidance unit is used to generate personalized health advice based on the assessment results, divide the oral deterioration risks into four categories according to the assessment results: severe risk, moderate risk, mild risk and no risk, and generate health guidance plans in text and voice forms for different risk levels.

2. A self-detection system for oral function impairment in the elderly according to claim 1, characterized in that: The mobile phone number verification module sends a verification code via SMS service. After the user enters the verification code, the system verifies its correctness to complete identity authentication; the basic information entry module performs a legitimacy check on the gender, date of birth, height and weight information entered by the user when registering; the historical data management module loads the user's historical test records from the database after the user logs in, and displays them in reverse chronological order. The user can click on a record to view detailed results and can modify the registration information.

3. The self-detection system for oral function impairment in the elderly according to claim 1, characterized in that: The dynamic logic jump module operation steps are as follows: S1. Let the problem set be Q = {Q1, Q2, ..., Q n }, where Q i Indicates a problem; S2. The jump rule for the problem is: Q i ·next question rules={(option1:Q j ),(option2:Q k ),...}; User selects option x After that, the next Q i for: next question id=Q i ·next question rules[option x ]; Among them, Q i ·next question rules means defining the next question jump path after the user selects different options; next question id means the next question ID calculated according to the user's selection, driving the dynamic adjustment of the evaluation process; options means the option list, loading the next question according to next_question_id, if next_question_id is empty, the evaluation ends, and the formula is used to determine ... question Q i Select option x , the system determines the next question Q by looking up the jump rule table j The ID of the 4. The self-detection system for oral function impairment in the elderly according to claim 1, characterized in that: The multimodal interaction module also includes a voice question and answer function and graphic and text auxiliary explanations. After the multimodal interaction module collects the user's voice input in real time through the device microphone, it calls the voice question and answer function to convert the voice stream into text. Then the multimodal interaction module matches the recognized text with the preset answer by keywords to mobilize the graphic and text auxiliary explanations. The multimodal interaction module loads graphic and text resources from the local cache according to the question ID, and embeds them into the specified area of ​​the interface for display.

5. The self-detection system for oral function impairment in the elderly according to claim 1, characterized in that: The question chain of the classification assessment module is designed based on the health behavior model and the health risk assessment theory, and the questions are designed in a hierarchical structure from general to specific. The health behavior model assesses the user's oral health care cognition and behavioral habits, and the health risk assessment theory collects data from the user's teeth, saliva and coordination dimensions to quantify the user's oral deterioration risk.

6. The self-detection system for oral function impairment in the elderly according to claim 1, characterized in that: The classification evaluation module receives the original data submitted by the user through the evaluation questionnaire unit for analysis, and the analysis steps are as follows: A1. Perform text conversion and semantic analysis on unstructured data, and perform standardized coding on structured data. If the user does not answer the required questions, the classification evaluation module triggers automatic reminders; A2. Extract key features from the preprocessed data according to the preset evaluation dimensions and assign weights to each feature; A3. Calculate the score of each dimension based on the characteristic value and weight, and apply the classification rules to determine the final risk level. The calculation formula for the final risk level is: Among them, Total Score represents the final risk level; Feature i Indicates characteristics; Weight i Represents the weight, and divides the risk level according to the calculated total interval: Severe risk: total score ≤ 40; Moderate risk: 40<total score≤60; Mild risk: 60<total score≤80; No risk: total score>80; A4. Cross-validate key dimensions to avoid single indicator bias, and match classification results with the intervention program library to generate personalized recommendations.

7. A self-detection method for oral function impairment in the elderly, according to the self-detection system for oral function impairment in the elderly according to claims 1-6, characterized in that: The steps include: B1. User registration and login: Enter the user's mobile phone number and send a verification code through a mobile terminal to complete identity authentication, collect basic user information, including gender, date of birth, height and weight, and perform legality verification, store user information and historical test records, and support viewing and modification after login; B2. Dynamic logic interactive assessment: questions are presented through a combination of voice playback and graphics, and users answer by checking options or voice input; B3. Multi-dimensional classification evaluation: Users answer questions in a chain and upload the current status of oral function to the self-test system for semantic analysis; B4. Risk grading and intervention generation: Based on the assessment results, the risk of oral function impairment is divided into four levels: severe, moderate, mild and no risk, and personalized health recommendations are generated for different levels; B5. Data synchronization and remote connection: User detection data is uploaded to the cloud, supporting simultaneous access on multiple devices.

8. A self-detection method for oral function impairment in the elderly according to claim 7, characterized in that: The multi-dimensional classification evaluation specifically evaluates the user's oral function status from five dimensions, and the five dimensions are: oral health status, oral coordination, oral health awareness, dietary rationality and exercise ability.

Images