Traditional Chinese medicine health-care artificial intelligence system for chronic diseases

Abstract

The invention relates to the technical field of chronic disease health care, and discloses a chronic disease traditional Chinese medicine health care artificial intelligence system, which comprises a cloud platform and an intelligent wearable device, the cloud platform and the intelligent wearable device are interconnected, and the cloud platform comprises an illness state analysis module, an input module, an output module, a docking module, an illness state information recording module and a safety protection module; the intelligent wearable device comprises an activation module, an information recording and storage module, a sorting module, a reminding module, a confirmation module, an unlocking and backup module, a voice broadcast module and a monitoring module. The chronic disease traditional Chinese medicine health-care artificial intelligence system can provide a health-care scheme suitable for a patient according to the condition of the patient, helps the patient to heal as soon as possible, can protect case information of the patient, avoids information leakage, prevents influence on the patient, and improves the patient health-care efficiency. Meanwhile, the patient can communicate with the medical staff in the recuperation stage, and the patient is further helped to be cured.

Description

Technical Field

[0001] The present invention relates to the technical field of chronic disease health care, and specifically to an artificial intelligence system for traditional Chinese medicine health care of chronic diseases. Background Art

[0002] Chronic diseases are full name of chronic non-communicable diseases. It does not refer to a specific disease, but a general term for a group of diseases with insidious onset, long course and persistent illness, lack of definite evidence of infectious biological etiology, complex etiology, and some of which have not been fully confirmed. Common chronic diseases mainly include cardiovascular and cerebrovascular diseases, cancer, diabetes, and chronic respiratory diseases.

[0003] With the development of technology, the information of patients will be saved on the cloud platform for subsequent medical staff to view in real time.

[0004] However, the communication between patients and medical staff exists in the hospital. When patients are recuperating in the hospital, medical staff can understand the information of patients through ward rounds. For some patients who do not need to be hospitalized for recuperation, medical staff cannot understand the information of patients at this time, and can only rely on the patients' own awareness to go to the hospital for reexamination, which is not conducive to the recovery of patients' conditions. At the same time, during the external recuperation period, a health care plan needs to be matched for assistance. Since patients cannot implement it consciously, the recovery effect is affected.

[0005] At the same time, according to a method and system for chronic patient information statistics management provided by application number CN202210989966.7, in the article, by establishing a patient file card, the status of the patient file card is updated in real time according to the data obtained from the detection end and the user end, and then the recuperation status of chronic patients is pre-identified with the help of intelligent devices, so that patients can clearly control their own recuperation status; in addition, the patient file card can be bound to the existing health code platform, and the implementation process is relatively easy.

[0006] However, although this system summarizes the patient information in an informatized manner, it has great defects in terms of information security. Since patients are relatively sensitive about their personal mentality and perception of the outside world during the recuperation period, if the patient information is leaked, it will make the recuperation process of patients more difficult and affect the overall recuperation course of patients.

[0007] Based on this, it is necessary to propose an artificial intelligence system for traditional Chinese medicine health care of chronic diseases. Summary of the Invention

[0008] In view of the deficiencies of the prior art, the present invention provides an artificial intelligence system for traditional Chinese medicine health care of chronic diseases, which has the advantage of being able to remind patients undergoing external recuperation to ensure that patients can execute the health care plan on time, and solves the problems raised in the background art.

[0009] The present invention provides the following technical solution: a traditional Chinese medicine health care artificial intelligence system for chronic diseases, including a cloud platform and intelligent wearable devices, where the cloud platform and the intelligent wearable devices are interconnected. The cloud platform includes: a disease analysis module, an input module, an output module, a docking module, a disease information recording module, and a security protection module. The intelligent wearable devices include: an activation module, an information recording and storage module, a sorting module, a reminder module, a confirmation module, an unlocking and backup module, a voice broadcast module, and a monitoring module.

[0010] Preferably, the input module: The patient uses a feature extraction algorithm for face recognition, the accuracy level of fingerprint recognition, and an algorithm type such as AES encryption for password encryption to input the patient's own situation into the background of the cloud platform, and establish the patient's own information. At the same time, the disease information diagnosed by the patient and the given health care plan are synchronously stored in the cloud platform. (Medical staff) combine their own information and input it into the cloud platform; the medical staff combine their own information and input it into the cloud platform. The output module: The medical staff can log in to the cloud platform through a feature extraction algorithm for face recognition, the accuracy level of fingerprint recognition, and an algorithm type such as AES encryption for password encryption, and can view the basic information of patients who have not recovered.

[0011] Preferably, the docking module: is used to record the information of patients and medical staff, and according to the logged-in information, the medical staff and patients responsible within the cloud platform form information docking and are synchronized to the corresponding medical staff list. The security protection module: Through the application of an intrusion detection system (IDS) and an intrusion prevention system (IPS), the information of patients and medical staff is encrypted and transmitted and stored through an SSL or TLS encryption protocol, and the information of patients and medical staff is automatically protected using RSA or ECC.

[0012] Preferably, the disease analysis module: uses (such as decision trees, neural networks, etc.) in combination with the chronic disease data stored in the cloud platform, the patient's diagnosis situation, the medical staff's diagnosis plan, and previous plans to accurately analyze the disease. The disease information recording module: is used to record the chronic disease case situations in the past, present, and future, as well as the patient information and the information of the responsible medical staff, and automatically accumulates as the disease data accumulates, and performs self-optimization and update, and then cooperates with the disease analysis module to accurately analyze and generate a health care plan.

[0013] Preferably, the activation module is used for the user to activate their own wearable device. The user can activate their own wearable device by entering their face and fingerprint. The information recording and storage module records the basic information of the patient (face, fingerprint, and the patient's diagnosis and rehabilitation plans transmitted by the cloud platform) and family member information through the table structure design of a relational database or the document structure of a non-relational database, and at the same time saves the data storage requirements through cloud storage services.

[0014] Preferably, the sorting module classifies the rehabilitation plans recommended by the cloud platform into early, middle, and late drug treatment forms and daily diet and exercise methods according to the severity of the disease or the characteristics of the drugs, and arranges the corresponding rehabilitation times at different stages. The reminder module records the rehabilitation stage plans and rehabilitation times arranged by the sorting module, and reminds the patient 20-30 minutes in advance in the form of (vibration, alarm, and voice broadcast).

[0015] Preferably, for the rehabilitation plans carried out by the patient at different stages, the (vibration, alarm, and voice broadcast) can only be turned off through the dual recognition of the patient's and family member's faces and fingerprints. The unlocking and backup module allows the user to unlock through their face and fingerprint for easy daily viewing. Family members can enter the wearable device through the backup face and fingerprint and view it at any time.

[0016] Preferably, the voice broadcast module allows the patient to broadcast their own situation by selecting the voice broadcast method, and family members can also view it through this method. The monitoring module can monitor the patient's exercise, heart rate, blood pressure, sleep quality, etc. during the rehabilitation stage in real time, and integrate the information into the information recording and storage module to facilitate automatic synchronization to the cloud platform when the wearable device is connected to the cloud platform later.

[0017] Preferably, the rehabilitation plan includes health care diet therapy, exercises, acupoint massage, health care tea drinks, etc. The rehabilitation plans for the patient's recovery are all stored on the cloud platform, and different plans are recommended according to different conditions. The smart wearable device includes: smart bracelets, smart watches, mobile phones, etc., which can all be used as carriers. The smart wearable device can be divided into the form of a host and a slave unit. The host and the slave unit synchronize information through network interconnection, which is based on the TCP / IP protocol. At the same time, distributed transaction processing is used to update the data, and Total Control software or AirDroid software is used to implement the permission management between the host and the slave unit.

[0018] Preferably, the cloud platform and the smart wearable device are configured through an interconnection module and a response module. The interconnection module: By means of Bluetooth, WIFI, and 5G communication interconnection, it is used to dock the cloud platform and the smart wearable device, enabling the automatic upload of the internal data of the smart wearable device to the cloud platform and performing periodic (three days or seven days) updates according to the patient's daily recuperation situation. The response module: The patient can upload the recuperation situation here, and the corresponding medical staff can receive this information through the cloud platform. The cloud platform automatically arranges according to the patient's emergency situation. The medical staff communicates with the patient (realizing voice and video based on the existing 5G communication technology framework), and at the same time encrypts this communication through physical layer encryption. The patient can make appropriate adjustments according to the suggestions given by the medical staff.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This kind of chronic disease traditional Chinese medicine health care artificial intelligence system can put forward a health care plan suitable for the patient according to the patient's own situation, help the patient recover as soon as possible, and at the same time can protect the patient's case information to avoid information leakage and prevent it from affecting the patient. At the same time, the patient can establish communication with the medical staff during the recuperation stage to further help the patient recover, and summarize and remind the patient's recuperation stage to avoid the patient missing the health care plan for different stages. At the same time, during the patient's recuperation stage, the family members can assist in supervising the patient to implement the health care plan. Through the joint efforts of the family members, medical staff, and the patient himself, the patient's recovery is guaranteed, and the function of the system is broadened.

[0020] In this kind of chronic disease traditional Chinese medicine health care artificial intelligence system, the concept of microservice architecture can be introduced into the system, and each functional module of the cloud platform and the smart wearable device can be split into independent microservices. The advantage of doing this is that each module can be independently developed, deployed, and upgraded, and will not affect the operation of the entire system due to problems in a certain module, and it is convenient to flexibly increase or decrease functions according to business needs. For example, the disease condition analysis module can be used as an independent microservice, which can quickly respond to data changes for analysis and calculation. At the same time, when the system needs to expand more analysis algorithms, only this microservice needs to be upgraded. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is a flowchart of the interconnection system between the cloud platform and the smart wearable device of the present invention; Figure 2 System diagram of the built-in modules of the cloud platform of the present invention; Figure 3 System diagram of the built-in modules of the intelligent wearable device of the present invention; Figure 4 Flowchart of personnel information input-output of the cloud platform of the present invention; Figure 5 Overall logic flowchart of the system of the present invention. Detailed implementation manners

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with 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. 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.

[0024] Please refer to Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 , a traditional Chinese medicine health care artificial intelligence system for chronic diseases, including a cloud platform and an intelligent wearable device, where the cloud platform and the intelligent wearable device are interconnected, The cloud platform includes: a disease analysis module, an input module, an output module, a docking module, a disease information recording module, and a security protection module; The disease analysis module is used to analyze the chronic disease information of the patient and at the same time give a health care plan; the input module and the output module are used to understand the information of medical staff and patients; the docking module is used to associate medical staff and patients to ensure the medical treatment efficiency; the disease information recording module: records the chronic disease information of the medical treatment and at the same time saves the health care plan; the security protection module: provides a protection mechanism in the form of a firewall to protect information.

[0025] The intelligent wearable device includes: an activation module, an information recording and storage module, a sorting module, a reminder module, a confirmation module, an unlocking and backup module, a voice broadcast module, and a monitoring module.

[0026] Activation module: used to activate the wearable device and simultaneously input the basic information of the user; Information recording and storage module: used to store the user information on the wearable device; Sorting module: sorts the health care plans by stage for the convenience of patients to execute; Reminder module: gives stage arrangements according to the sorting module and makes corresponding reminders to ensure that patients can execute normally; Confirmation module: used to confirm whether the patient executes the health care plan normally; Unlock and backup module: used to unlock the wearable device; Voice broadcast module: can broadcast the patient's own situation and the stage health care plan to facilitate the patient's understanding; Monitoring module: detects the patient's situation.

[0027] This chronic disease traditional Chinese medicine health care artificial intelligence system aims to integrate traditional Chinese medicine theoretical systems such as meridians, qi and blood, and zang-fu theory, etc. It uses advanced artificial intelligence algorithms to collect and analyze patients' health data (including but not limited to traditional Chinese medicine diagnosis data, western medicine physical examination data, lifestyle data, etc.), and customize personalized traditional Chinese medicine health care plans for patients with various chronic diseases (specifically listed as common chronic diseases such as hypertension, diabetes, coronary heart disease, etc.), covering aspects such as diet conditioning, exercise guidance, traditional Chinese medicine prescription recommendation, and traditional Chinese medicine physiotherapy advice, so as to achieve all-round and precise traditional Chinese medicine health care services for chronic diseases.

[0028] Furthermore, the intelligent wearable device is used to collect data such as the patient's exercise steps, heart rate, sleep quality, etc.; Traditional Chinese medicine special diagnostic equipment (such as tongue image instrument, pulse condition instrument, etc.) collects traditional Chinese medicine characteristic diagnostic data such as tongue image and pulse condition; It may also include test report data generated by western medicine examination equipment in the hospital; And the intelligent wearable device collects exercise and heart rate data in real time every 5 minutes, stores them in JSON format, and saves them in the distributed database of the system.

[0029] As a preferred technical solution of the present invention, the input module: the patient inputs his own situation into the background of the cloud platform by using the feature extraction algorithm of face recognition, the accuracy level of fingerprint recognition, and the algorithm type of password encryption such as AES encryption, and establishes his own information data, and simultaneously stores the patient's diagnosed disease information and the given health care plan in the cloud platform synchronously. (Medical staff) combines their own information and inputs it into the cloud platform; The medical staff combines their own information and inputs it into the cloud platform. The output module: The medical staff can log in to the cloud platform by using the feature extraction algorithm of face recognition, the accuracy level of fingerprint recognition, and the algorithm type of password encryption such as AES encryption, and can view the basic information of patients who have not recovered.

[0030] Among them: In addition to the existing face recognition, fingerprint recognition, and password methods, the input module can introduce voiceprint recognition technology. Voiceprint recognition has uniqueness and convenience. Each person's voiceprint is unique and there is no need to contact the device. By using a deep learning voiceprint recognition algorithm, it can effectively improve the accuracy and security of identity verification. At the same time, during the data transmission process, the SSL / TLS encryption protocol is used to ensure that the information of patients and medical staff is not stolen or tampered with during network transmission.

[0031] As a preferred technical solution of the present invention, the docking module: is used to record the information of patients and medical staff, and based on the logged-in information, the medical staff and patients responsible within the cloud platform form information docking and synchronize to the corresponding medical staff list. The security protection module: through the application of intrusion detection system (IDS) and intrusion prevention system (IPS), encrypts and transmits and stores the information of patients and medical staff through the SSL or TLS encryption protocol, and uses RSA or ECC to automatically protect the information of patients and medical staff.

[0032] Among them: On the basis of the existing docking function, blockchain technology is added. By using the distributed ledger feature of blockchain, record the information docking process of patients and medical staff, ensure the immutability and traceability of information. Each docking operation will be recorded on the blockchain, forming a complete operation chain. When disputes occur or audits are needed, the information of each link can be clearly queried.

[0033] As a preferred technical solution of the present invention, the disease condition analysis module: adopts (such as decision trees, neural networks, etc.) combined with the chronic disease data, patient diagnosis situations, medical staff diagnosis plans, and previous plans stored in the cloud platform to accurately analyze the disease condition. The disease condition information recording module: is used to record the chronic disease case situations in the past, present, and future, as well as the patient information and the information of the responsible medical staff, and automatically accumulates as the disease condition data accumulates, and performs self-optimization and update, and then cooperates with the disease condition analysis module to accurately analyze and generate a health care plan.

[0034] Furthermore, when formulating a diet regulation plan, based on the theory of the five flavors entering the five zang-organs in traditional Chinese medicine, for hypertensive patients, if they are dialectically diagnosed as the type of hyperactivity of liver-yang, according to the theory that sour flavor enters the liver and can astringe liver-yang, it is recommended to eat an appropriate amount of sour foods such as hawthorn; in terms of exercise guidance, referring to the theory of seasonal health preservation in traditional Chinese medicine, as all things grow in spring, it is recommended that patients do more outdoor stretching exercises, such as Baduanjin and Taijiquan, to conform to the rising of yang qi; at the same time, mainly relying on formalizing the rules of traditional Chinese medicine dialectics, constructing a corresponding knowledge base, and using the knowledge graph technology of artificial intelligence to associate different symptoms, signs with the results of traditional Chinese medicine dialectics, so as to provide a basis for the generation of subsequent health care plans.

[0035] The specific content and form of a specific health care plan, such as "for a 55-year-old patient with type 2 diabetes and a traditional Chinese medicine syndrome differentiation of qi and yin deficiency, the personalized health care plan systematically generated includes: in terms of diet, it is recommended to consume 50-100 grams of Chinese yam daily to replenish qi and nourish yin, and be paired with 100-150 grams of balsam pear to assist in reducing blood sugar; in terms of exercise, it is recommended to practice yoga 3-5 times a week, 30-45 minutes each time, to regulate the body and mind and enhance physical fitness; the traditional Chinese medicine prescription recommends modified Shengmaiyin, and the specific formula is 15 grams of Codonopsis pilosula, 12 grams of Ophiopogon japonicus, 9 grams of Schisandra chinensis, 20 grams of Astragalus membranaceus, etc., one dose per day, taken in two divided doses; traditional Chinese medicine physiotherapy recommends massaging the Zusanli acupoints 2-3 times a week, massaging each acupoint on each side for 10-15 minutes each time, to invigorate the spleen and replenish qi and harmonize qi and blood".

[0036] Among them: Disease analysis module: Existing disease analysis technologies often have difficulty accurately integrating traditional Chinese medicine theory with a large amount of case data. To solve this problem, this system can adopt a model that combines convolutional neural network (CNN) and long short-term memory network (LSTM) in deep learning. CNN is good at extracting features in data such as images and can be used to analyze information such as tongue images and face diagnosis in traditional Chinese medicine; LSTM has good processing ability for sequence data and can analyze the development trend of the patient's condition. By combining the two and integrating the knowledge graph of classic traditional Chinese medicine theory, through continuously learning a large amount of case data of traditional Chinese medicine chronic diseases, it can more accurately formulate personalized health care plans for patients.

[0037] Furthermore, the system uses convolutional neural network (CNN) in deep learning to extract features from tongue image to assist in tongue diagnosis and syndrome differentiation in traditional Chinese medicine; uses support vector machine (SVM) algorithm to classify pulse data and judge the type of pulse. It also includes the source of the training data set (such as case data and volunteer data collected from multiple traditional Chinese medicine hospitals), scale (number of cases, amount of data, etc.), and how to preprocess the data set (such as data cleaning, standardization, etc.) and verification (way of cross-validation and specific parameter settings).

[0038] Furthermore, the medical staff information in the cloud platform is divided into different types according to different pathologies. A group of medical staff under the same type is responsible for 5-10 groups of patients. Each group of patients can monitor the health care progress of the patients through the combination of personnel shift and system monitoring; If a patient has two or more pathological characteristics, one or two medical staff under this pathological characteristic will be responsible for this type of patient in a cooperative combination manner to ensure that the patient can form timely information docking.

[0039] Specifically, based on multi-dimensional information such as the patient's disease type, traditional Chinese medicine syndrome differentiation results, age, gender, and living habits, a combination of diet, exercise, traditional Chinese medicine, physical therapy, etc. that meet the conditions is screened from a pre-constructed health preservation knowledge base, and is personalized adjusted according to a specific weight calculation method to finally generate a personalized health preservation plan.

[0040] This system deeply integrates the traditional Chinese medicine theory of the five evolutive phases and six climatic factors with artificial intelligence algorithms. By analyzing the changing laws of the five evolutive phases and six climatic factors and the individual physical differences of patients, it can predict in advance the onset risks of chronic diseases in different seasons, and accordingly formulate prospective health preservation prevention measures. This method has not been reported in the existing field of traditional Chinese medicine health preservation for chronic diseases. In addition, the system has developed a brand-new data fusion algorithm with Chinese medicine characteristics, which can efficiently integrate various traditional Chinese medicine diagnosis data such as tongue images and pulse conditions with western medicine physical examination data to achieve more accurate disease analysis and health preservation plan formulation. Compared with the systems that analyze traditional single data types, it has significant advantages. Compared with some existing systems that only formulate health preservation plans based on western medicine indicators, after integrating traditional Chinese medicine theories and data, this system can start from the overall concept, consider the yin-yang balance and qi-blood meridian state of the human body, making the health preservation plan more targeted and comprehensive. Compared with some systems that simply apply traditional Chinese medicine knowledge, the artificial intelligence algorithm fusion method of this system is more advanced, can handle more complex data relationships, and provide more accurate personalized plans.

[0041] As a preferred technical solution of the present invention, the activation module: is used for the user to activate their own wearable device. The user can activate their own wearable device by inputting facial features and fingerprints. The information recording and storage module: is used to record the patient's basic information (facial features, fingerprints, and the patient's diagnosis plan and health preservation plan transmitted by the cloud platform) and family member information through the table structure design of a relational database or the document structure of a non-relational database, and at the same time save the data storage requirements through cloud storage services.

[0042] As a preferred technical solution of the present invention, the sorting module: classifies the health preservation plans into early, middle, and late drug treatment forms and usual diet and exercise methods according to the severity of the disease or the characteristics of the drugs based on the health preservation plans recommended by the cloud platform, and arranges the corresponding health preservation times at different stages. The reminder module: records the health preservation stage plans and health preservation times arranged by the sorting module, and reminds the patient 20 - 30 minutes in advance in the form of (vibration, alarm, and voice broadcast) according to this time point.

[0043] As a preferred technical solution of the present invention, the confirmation module: the rehabilitation plan carried out by the patient at different stages can be closed (vibration, alarm and voice broadcast) only through the dual recognition of the patient's and family member's faces and fingerprints. The unlocking and backup module: the user can unlock through the face and fingerprint, so as to facilitate daily viewing. The family member can enter the wearable device through the backup face and fingerprint and view it at any time.

[0044] Among them: the unlocking and backup module: on the basis of face and fingerprint unlocking, iris recognition technology is added. Iris recognition has extremely high security and accuracy, and its unique texture features hardly change with time and environment. At the same time, for the backup data, end-to-end encryption technology is adopted to ensure the maximum security of the data when the family member views the backup information.

[0045] As a preferred technical solution of the present invention, the voice broadcast module: the patient can choose the voice broadcast method to broadcast his own situation, and the family member can also view it through this method. The monitoring module: can monitor the patient's exercise situation, heart rate situation, blood pressure and sleep quality during the recuperation stage in real time, and integrate the information into the information recording and storage module, which is convenient for automatic synchronization to the cloud platform when the subsequent wearable device is docked with the cloud platform.

[0046] Among them: the monitoring module can adopt more advanced biosensor technologies, such as optical heart rate sensors and piezoelectric blood pressure sensors. The optical heart rate sensor can monitor the heart rate in real time by measuring the light reflection of blood vessels under the skin. By using high-resolution sensors and advanced signal processing algorithms, it can capture heart rate changes more accurately. The piezoelectric blood pressure sensor calculates blood pressure by measuring pressure changes and can achieve more accurate blood pressure measurement. In addition, in terms of sleep quality monitoring, combining body movement sensors and electroencephalogram monitoring technologies can not only judge the sleep duration, but also analyze the depth and quality of sleep, providing more comprehensive data support for the adjustment of the rehabilitation plan.

[0047] As a preferred technical solution of the present invention, the rehabilitation plan includes health care diet therapy, exercises, acupoint massage, health care tea drinks, etc. The rehabilitation plans for the patient's recovery are all stored on the cloud platform, and different plans are recommended according to different conditions. The intelligent wearable device includes: intelligent bracelets, intelligent watches, mobile phones, etc. can all be used as carriers. The intelligent wearable device can be divided into the form of a host and a slave unit. The host and the slave unit synchronize information through network interconnection, which is based on the TCP / IP protocol. At the same time, distributed transaction processing is used to realize data update, and Total Control software or AirDroid software is used to realize the permission management between the host and the slave unit.

[0048] The above-mentioned host intelligent wearable device is used by patients, and the extension is used by the patient's family members. Since the intelligent wearable device needs to be logged in through verification, the login methods of the host and the extension are the same. At the same time, the extension is held by the primary family member and the secondary family member. The permissions held by the primary family member include the patient's diagnosis records, rehabilitation plans, execution times, information of the connected medical staff, and ecological changes during the patient's rehabilitation period. The permissions held by the secondary family member include the patient's rehabilitation plan and execution time; During the activation phase of the host and the extension, it is judged according to the immediate family members and secondary family members. At the same time, the family member information of both categories is synchronized and bound to the patient information in the host. The immediate family members hold the primary extension, and the secondary family members hold the secondary extension. Among them, the host, the primary extension, and the secondary extension obtain corresponding permissions through the method of identity verification and authorization; For example: when the primary extension needs to obtain the host permissions, it identifies the face of the person holding the primary extension and compares it with the face of the primary extension stored in the host. When the comparison is consistent, the patient information in the host can be accessed through the holder of the primary extension. When the secondary extension needs to access, it is jointly executed through face comparison and information authorization of the primary extension to ensure that information leakage does not occur.

[0049] As a preferred technical solution of the present invention, the cloud platform and the intelligent wearable device are configured through an interconnection module and a response module. The interconnection module: through the interconnection methods of Bluetooth, WIFI, and 5G communication, it is used to connect the cloud platform and the intelligent wearable device, realize the automatic upload of the internal data of the intelligent wearable device to the cloud platform, and update it periodically (every three days or seven days) according to the patient's daily recuperation situation. The response module: the patient can upload the recuperation situation here, and the corresponding medical staff receives this information through the cloud platform. The cloud platform automatically arranges according to the patient's emergency situation. The medical staff communicates with the patient (realize voice and video based on the existing 5G communication technology framework), and at the same time encrypts this communication through physical layer encryption. The patient can make appropriate adjustments according to the suggestions given by the medical staff.

[0050] Furthermore, for the data collection part: when collecting multi-source heterogeneous data of traditional Chinese medicine and Western medicine, a new data counting fusion algorithm is used. For example, the tongue image and pulse condition data of traditional Chinese medicine are very different in structure and type from the test reports and imaging data of Western medicine. The innovative algorithm can construct a unified data representation space, accurately count and conduct correlation analysis on the key features of data from different sources. Taking diabetes as an example, it combines the counting of tongue image features of traditional Chinese medicine (such as the quantitative counting of tongue coating thickness and color change) with the numerical counting of indicators such as blood sugar and glycated hemoglobin in Western medicine to more comprehensively reflect the patient's health status; Using streaming computing technology, achieve dynamic real-time counting of patients' health data. For data such as the number of steps and heart rate collected in real time by smart wearable devices, the streaming counting method can capture the changing trends of the data in a timely manner. For example, when a patient is exercising, the system can count the number of heart rate changes per minute in real time, and make a counting judgment based on the set threshold. If the number of abnormal heart rate changes exceeds a certain count within a short period of time, the system can immediately issue a warning and provide timely adjustment suggestions for the patient.

[0051] Regarding the data analysis part: Construct a traditional Chinese medicine knowledge graph to associate information such as traditional Chinese medicine theory, diseases, and prescriptions in the form of a graph. When analyzing data, use the graph structure for counting reasoning. For example, when conducting traditional Chinese medicine syndrome differentiation for patients with hypertension, the system can search for relevant nodes in the knowledge graph based on the patients' symptoms, and judge the most suitable syndrome differentiation type by counting the number and weights of symptom nodes associated with different syndrome differentiation types. If the count of symptom nodes related to the syndrome differentiation of hyperactivity of liver yang, such as dizziness, headache, and flushed face and red eyes, reaches a certain proportion, the system can tend to this syndrome differentiation result, providing a precise basis for formulating subsequent health preservation plans; When using a deep learning model to analyze data, introduce feature counting optimization technology. For example, when analyzing traditional Chinese medicine image data (such as tongue image), the traditional convolutional neural network model may have problems such as incomplete or redundant feature extraction. The innovative method can screen the feature maps output by the convolutional layer through counting, retain the features with high counting importance, and remove the noise features with low counting contributions, improving the recognition accuracy of the model for traditional Chinese medicine disease symptoms, and thus enhancing the reliability of data analysis.

[0052] Regarding the program evaluation part: Establish a quantitative counting evaluation system for the health preservation effect based on multi-dimensional indicators. Conduct comprehensive counting evaluations from aspects such as the improvement of traditional Chinese medicine symptoms (such as the count of symptom alleviation and the count of symptom disappearance), the changes in western medicine physiological indicators (such as the count of blood pressure and blood sugar reduction), and the improvement of the patient's quality of life (such as the count of improved sleep quality days and the count of good mental state days). By setting the weights of different indicators and calculating the comprehensive health preservation effect score, it is possible to evaluate the actual effect of the health preservation plan more objectively and comprehensively, providing a strong basis for the adjustment and optimization of the plan; Apply reinforcement learning technology and regard the implementation process of the health preservation plan as a decision-making process. The system conducts counting learning based on the feedback after each implementation of the health preservation plan (obtained through the above-mentioned quantitative counting evaluation system for the health preservation effect). For example, if a certain plan enables the count of symptom improvement in patients to reach a certain goal, a positive reward is given; otherwise, a negative reward is given. Through continuous iterative counting, the system can automatically adjust the parameters and content of the health preservation plan, and gradually explore the personalized health preservation plan most suitable for the patient, realizing the dynamic optimization and continuous improvement of the plan.

[0053] The reminder module also includes a reminder to record the patient's review time after a period of staged recuperation, so that medical staff can adjust the patient's health care plan in a targeted manner, and can add an intelligent interactive reminder function. When the patient does not implement the health care plan on time, the reminder module can have a simple conversation with the patient through the intelligent voice interaction system to understand the reason why the patient did not implement it, and give corresponding suggestions or encouragement according to the situation. For example, if the patient says he forgot, the system can simply remind the importance of the plan; if the patient has special circumstances, the system can feedback the information to the medical staff; Data management and security protection Data management: Establish a data warehouse to uniformly manage the data collected by the cloud platform and smart wearable devices. Use big data technologies, such as Hadoop and Spark frameworks, to store, process and analyze massive amounts of data. Through data mining algorithms, discover potential patterns and trends from a large amount of case data, and provide more valuable references for disease analysis and the formulation of health care plans. At the same time, establish a data quality management mechanism to monitor and verify the accuracy, completeness and consistency of data in real time, and promptly discover and correct errors in the data.

[0054] Security protection: In the security protection module, in addition to firewall-like protection, an AI-driven security protection system is introduced to monitor network traffic in real time using machine learning algorithms. By establishing a normal behavior model, it identifies abnormal network activities, such as hacker attacks, data leaks, and other behaviors, and takes corresponding protective measures in a timely manner, such as blocking abnormal connections, isolating infected devices, etc. In addition, the system is regularly scanned for vulnerabilities and security assessments are conducted to promptly repair discovered security vulnerabilities.

[0055] Through the above comprehensive improvement from the technical level, this chronic disease Chinese medicine health care artificial intelligence system will be significantly improved in terms of architectural flexibility, functional accuracy, data management and security protection, making it more competitive among similar patents and expected to gain wider application and recognition.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence system for traditional Chinese medicine health care for chronic diseases, including a cloud platform and a smart wearable device, characterized in that: The cloud platform and the smart wearable device are interconnected. The cloud platform includes: a disease analysis module, an input module, an output module, a docking module, a disease information recording module and a safety protection module; The smart wearable device includes: an activation module, an information recording and storage module, a sorting module, a reminder module, a confirmation module, an unlocking and backup module, a voice broadcast module and a monitoring module.

2. According to claim 1, the artificial intelligence system for traditional Chinese medicine health care for chronic diseases is characterized by: The input module: the patient uses the feature extraction algorithm of facial recognition, the accuracy level of fingerprint recognition, and the algorithm type of password encryption such as AES encryption to input the patient's own situation into the background of the cloud platform, and establish the patient's own information data. At the same time, the patient's diagnosed condition information and the given health care plan are synchronously stored on the cloud platform. (Medical staff) combine their own information and input it into the cloud platform; medical staff combine their own information and input it into the cloud platform. The output module: medical staff can log in to the cloud platform through the feature extraction algorithm of facial recognition, the accuracy level of fingerprint recognition, and the algorithm type of password encryption such as AES encryption, and can view the basic information of unrecovered patients.

3. According to claim 1, the artificial intelligence system for traditional Chinese medicine health care for chronic diseases is characterized by: The docking module is used to record the information of patients and medical staff, and based on the login information, the responsible medical staff and patients in the cloud platform form information docking and synchronize them to the corresponding medical staff list. The security protection module uses the intrusion detection system (IDS) and intrusion prevention system (IPS) to encrypt, transmit and store the patient and medical staff information through the SSL or TLS encryption protocol, and automatically protects the patient information and medical staff information using RSA or ECC.

4. According to claim 1, the artificial intelligence system for traditional Chinese medicine health care for chronic diseases is characterized by: The condition analysis module: uses (such as decision trees, neural networks, etc.) combined with chronic disease information, patient diagnosis conditions, medical diagnosis plans and past plans stored on the cloud platform to accurately analyze the condition. The condition information recording module: is used to record past, present and future chronic disease conditions, as well as patient information and responsible medical staff information, and automatically accumulates as the condition data accumulates, and performs self-optimization and updating, and then cooperates with the condition analysis module to accurately analyze the production of health care plans.

5. According to claim 1, the artificial intelligence system for traditional Chinese medicine health care for chronic diseases is characterized by: The activation module is used for users to activate their own wearable devices. Users can activate their own wearable devices by entering their faces and fingerprints. The information recording and storage module is used to record the patient's basic information (face, fingerprints, and patient diagnosis and health care plans transmitted by the cloud platform) and family information through the table structure design of a relational database or the document structure of a non-relational database, and save data storage needs through cloud storage services.

6. According to claim 1, the artificial intelligence system for traditional Chinese medicine health care for chronic diseases is characterized by: The sorting module: according to the health care plan recommended by the cloud platform, the health care plan is divided into early, mid-day and evening drug treatment forms and usual diet and exercise methods according to the severity of the disease or the characteristics of the medicine, and the corresponding health care time is arranged in different stages. The reminder module: records the health care stage plan and health care time arranged by the sorting module, and according to the time point, reminds the patient 20-30 minutes in advance through (vibration, alarm and voice broadcast).

7. According to claim 1, the artificial intelligence system for traditional Chinese medicine health care for chronic diseases is characterized by: The confirmation module: the health care plan for patients at different stages can be turned off (vibration, alarm and voice broadcast) only after dual recognition of the patient's and family's face and fingerprint. The unlocking and backup module: the user can unlock by face and fingerprint, which is convenient for daily viewing. Family members can enter the wearable device through the backup face and fingerprint and can view it at any time.

8. The artificial intelligence system for traditional Chinese medicine health care for chronic diseases according to claim 1 is characterized by: The voice broadcast module: the patient can choose the voice broadcast method to broadcast his own condition, and the family members can also view it in this way. The monitoring module: can monitor the patient's exercise condition, heart rate, blood pressure and sleep quality during the convalescent stage in real time, and integrate the information into the information recording and storage module, so that it can be automatically synchronized to the cloud platform when the wearable device and the cloud platform are connected in the future.

9. The artificial intelligence system for traditional Chinese medicine health care for chronic diseases according to claim 1 is characterized by: The health care program includes health food therapy, exercises, acupoint massage, health tea, etc. The health care programs for patient recovery are stored on the cloud platform, and different programs are recommended according to different conditions. The smart wearable devices include: smart bracelets, smart watches and mobile phones, etc., which can all be used as carriers. The smart wearable devices can be divided into host and extension forms. The host and extension are synchronized through network interconnection. It is established under the TCP / IP protocol and uses distributed transaction processing to realize data updates. Total Control software or AirDroid software is used to realize permission management between the host and extension.

10. The artificial intelligence system for traditional Chinese medicine health care for chronic diseases according to claim 1 is characterized by: The cloud platform and the smart wearable device are configured through an interconnection module and a response module. The interconnection module is used to connect the cloud platform and the smart wearable device through Bluetooth, WIFI and 5G communication interconnection, so as to realize automatic uploading of internal data of the smart wearable device to the cloud platform, and perform periodic (three or seven days) updates according to the patient's daily recuperation condition. The response module: the patient can upload the recuperation condition there, and the corresponding medical staff will receive the information through the cloud platform. The cloud platform will automatically arrange according to the patient's emergency situation. The medical staff will communicate with the patient (based on voice and video under the existing 5G communication technology framework), and encrypt the communication through physical layer encryption. The patient can make appropriate adjustments according to the suggestions given by the medical staff.

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