Diabetic foot health management system based on cloud computing

Abstract

The invention discloses a diabetic foot health management system based on cloud computing, which belongs to the technical field of diabetic foot health management and comprises a cloud computing platform, a monitoring module and a user display module. The cloud computing platform comprises a monitoring analysis module, a data analysis module and a guidance module; the monitoring analysis module is used for determining a target monitoring scheme of a patient and sending the target monitoring scheme to the monitoring module; the data analysis module is used for analyzing the state monitoring data of the patient to obtain state result data and sending the state result data to the user display module; the monitoring module is used for monitoring the state of the patient according to the target monitoring scheme, obtaining corresponding state monitoring data and sending the state monitoring data to the cloud computing platform; the user display module is used for displaying data, receiving state result data and displaying the state result data to a user; the guidance module is used for performing guidance processing according to the guidance demand of the patient.

Description

Technical Field

[0001] The present invention belongs to the technical field of diabetic foot health management, and specifically relates to a diabetic foot health management system based on cloud computing. Background Art

[0002] Diabetic foot is a serious complication of diabetic patients, with a complex pathogenesis involving multiple aspects such as neuropathy, angiopathy, and infection. Due to the long-term hyperglycemic state of diabetic patients, the peripheral nerves and blood vessels are damaged, resulting in reduced or lost foot sensation and poor blood circulation, thereby increasing the risk of injury and infection. Once a foot trauma or infection occurs, it is often difficult to heal, easily leading to serious consequences such as ulcers and gangrene, and even requiring amputation treatment.

[0003] Currently, the treatment and management of diabetic foot mainly rely on traditional medical means such as drug treatment, surgical treatment, and rehabilitation training. However, these traditional means have many deficiencies. For example, in terms of health management, it is difficult for traditional health management to provide services to patients in a timely and convenient manner; the condition is likely to deteriorate due to inadequate management.

[0004] Based on this, in order to solve the problem of diabetic foot health management, the present invention provides a diabetic foot health management system based on cloud computing. Summary of the Invention

[0005] In order to solve the problems existing in the above solutions, the present invention provides a diabetic foot health management system based on cloud computing.

[0006] The object of the present invention can be achieved by the following technical solutions:

[0007] A diabetic foot health management system based on cloud computing includes a cloud computing platform, a monitoring module, and a user display module;

[0008] The cloud computing platform includes a monitoring and analysis module, a data analysis module, and a guidance module;

[0009] The monitoring and analysis module is used to determine the target monitoring plan of the patient and send the target monitoring plan to the monitoring module.

[0010] Furthermore, the method for determining the target monitoring plan includes:

[0011] Set up a monitoring parameter table, which is used to count the monitoring items required for diabetic foot monitoring and the monitoring requirement labels of the monitoring items for different health stages. The monitoring requirement labels include necessary labels, optional labels, and unnecessary labels;

[0012] Identify the health stage of the patient, match the corresponding necessary monitoring items and optional monitoring items from the monitoring parameter table according to the health stage, display the necessary monitoring items and optional monitoring items to the user, and let the user determine each monitoring parameter item to be monitored;

[0013] Analyze various candidate monitoring methods for the monitoring parameter items, screen the candidate monitoring methods, and obtain the target monitoring plan.

[0014] Furthermore, the method for screening the candidate monitoring methods includes:

[0015] Combine the candidate monitoring methods according to the monitoring parameter items to form several candidate monitoring plans; conduct simulation analysis on the candidate monitoring plans to obtain the corresponding estimated costs and additional simulation values;

[0016] Calculate the screening value of the candidate monitoring methods according to the screening formula, and the screening formula is:

[0017] SA = b1×CB + b2×FA;

[0018] In the formula: SA is the screening value; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 ≤ b2 ≤ 1; FA is the additional influence value;

[0019] Determine the target monitoring plan according to the screening value.

[0020] The data analysis module is used to analyze the status monitoring data of the patient to obtain status result data, and the status result data includes the health stage, potential risks and health management plans; send the status result data to the user display module respectively.

[0021] Furthermore, the method for determining the health stage includes:

[0022] Preset corresponding stage recognition features for all health stages; establish corresponding stage recognition models according to the stage recognition features, and the expression of the stage recognition model is:

[0023]

[0024] In the formula: (HZ, TP i ) is the input data, HZ is the status monitoring data; TP i represents the stage recognition feature of the corresponding health stage, i represents the corresponding health stage, i = 1, 2,..., n, n is the number of health stages; HZ → TP i means that the status monitoring data conforms to the stage recognition feature of the corresponding health stage; the output data is the stage recognition value DS(HZ, TP i ), and the stage recognition value is 1 or 0;

[0025] Analyze the status monitoring data through the stage recognition model to obtain the stage recognition value corresponding to the corresponding health stage, and determine the health stage of the patient according to the stage recognition value.

[0026] The monitoring module is used to monitor the patient according to the target monitoring plan, obtain the corresponding status monitoring data, and send the status monitoring data to the cloud computing platform.

[0027] Furthermore, assist the user in monitoring management according to the target monitoring plan.

[0028] Furthermore, the method for assisting the user in monitoring management according to the target monitoring plan includes:

[0029] Establish a reservation judgment model, and the expression of the reservation judgment model is:

[0030]

[0031] In the formula: S is the target monitoring plan; the output data is the reservation judgment value YP(S), and the reservation judgment value is 1 or 0;

[0032] Analyze the target monitoring plan through the reservation judgment model to obtain the corresponding reservation judgment value;

[0033] When the reservation judgment value is 0, no corresponding processing is performed;

[0034] When the reservation judgment value is 1, identify the reservation event information according to the target monitoring plan, perform monitoring reservation processing according to the reservation event information, generate reservation prompt data, and perform prompt processing according to the reservation prompt data.

[0035] The user display module is used to display data, receive the status result data, and display the status result data to the user.

[0036] The guidance module is used to perform guidance processing according to the guidance needs of the patient.

[0037] Furthermore, the working method of the guidance module includes:

[0038] Establish an information repository, which is used to store guidance personnel information; the platform party presets a number of status reference standards, and sets feature collection items according to the status reference standards;

[0039] Perform real-time feature collection on the patient according to the feature collection items, obtain the patient feature data, match the patient feature data with the status reference standards, determine the status reference standard to which the patient belongs, and label the patient with the corresponding status reference standard;

[0040] When the user has a need for guidance, generate the patient's condition data based on the patient's status result data and status monitoring data;

[0041] Match the information of the guidance personnel who meet the guidance needs from the information repository; screen the guidance personnel to determine several candidate guidance personnel; display the guidance personnel information of the candidate guidance personnel to the user, and let the user determine the target guidance personnel; send the patient's condition data and guidance needs to the target guidance personnel, and let the target guidance personnel conduct guidance processing on the patient.

[0042] Further, the method for screening the guidance personnel includes:

[0043] Obtain the score of the guidance personnel in real time; identify the number of times the guidance personnel has guided the patient;

[0044] Calculate the screening value of the guidance personnel according to the screening formula, and the screening formula is:

[0045] PU = b3×PF + b4×ln(CN + 1);

[0046] In the formula: PU is the screening value; b3 and b4 are both proportionality coefficients, and the value range is 0 < b3 ≤ 1, 0 ≤ b4 ≤ 1; PF is the score; CN is the number of guidance times;

[0047] Determine the candidate guidance personnel according to the screening value.

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] By performing real-time monitoring and analysis on the patient's condition, dynamically adjust the patient's target monitoring plan, enabling monitoring to be carried out according to the actual situation of the patient, and at the same time providing auxiliary management for patient monitoring to achieve intelligent services; to solve the timeliness problem of out-of-hospital rehabilitation management, through the guidance module, quickly conduct guidance processing on the patient, enabling the guidance personnel to quickly understand the patient's status, facilitating guidance processing, and avoiding delaying the patient's treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0051] Figure 1 It is the principle block diagram of the present invention;

[0052] Figure 2 It is the working flowchart of the present invention. Detailed implementation mode

[0053] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0054] As Figures 1 to 2 shown, the diabetic foot health management system based on cloud computing includes a cloud computing platform, a monitoring module, and a user display module;

[0055] The cloud computing platform is responsible for receiving, storing, and processing data, including a monitoring and analysis module, a data analysis module, and a guidance module;

[0056] The monitoring and analysis module is used to determine the target monitoring plan for the patient and send the target monitoring plan to the monitoring module; the user makes monitoring preparations according to the target monitoring plan.

[0057] In one embodiment, the target monitoring plan can be determined by a doctor's recommendation, the patient's self-determined purchase, etc.

[0058] In one embodiment, the method for determining the target monitoring plan includes:

[0059] Set various monitoring data that may be required for the treatment and monitoring of diabetic foot, and statistically form a monitoring parameter table. The monitoring parameter table is used to count various monitoring items and the monitoring requirement labels of the monitoring items for different health stages. The monitoring requirement labels include necessary labels, optional labels, and unnecessary labels, that is, the monitoring parameters of the monitoring items corresponding to the necessary labels must be monitored at this health stage; the optional label is to selectively choose whether to monitor according to the actual situation of the patient. If the economic ability is sufficient, monitoring can be selected, otherwise it can be not monitored; the unnecessary label means that the patient does not need to monitor; due to differences in different severities, economic abilities, etc., the parameters that need to be monitored will be different; the specific monitoring parameter table is set by the platform side and professionally demonstrated; the health stage therein is uniformly adapted to the health stage determined by subsequent analysis;

[0060] Identify the patient's health stage, such as the specific stages corresponding to the non-ulcer stage and ulcer stage of diabetic foot; initially determined according to the doctor's diagnosis, and the corresponding health stage is determined by the data analysis module subsequently; match the corresponding necessary monitoring items and optional monitoring items from the monitoring parameter table according to the health stage, display the necessary monitoring items and optional monitoring items to the user, and the user determines each monitoring item to be monitored and marks it as a monitoring parameter item;

[0061] Analyze various candidate monitoring methods based on the monitoring parameter items, such as intelligent wearable devices like intelligent sole shoes, mobile phone captured images, community hospital detections, and other optional methods that can achieve the monitoring of corresponding monitoring parameter items, and mark them as candidate monitoring methods;

[0062] Screen the candidate monitoring methods to determine the target monitoring plan for monitoring each monitoring parameter item.

[0063] In one embodiment, screening the candidate monitoring methods can be analyzed based on the current screening method, priority algorithm, etc.

[0064] In one embodiment, the method for screening the candidate monitoring methods includes:

[0065] Combine the candidate monitoring methods according to the monitoring parameter items to form several candidate monitoring plans, that is, each candidate monitoring plan can achieve the monitoring of all monitoring parameter items;

[0066] Conduct simulation analysis on the candidate monitoring plans to obtain the corresponding estimated cost and estimated duration. The estimated duration can be simulated according to a monitoring cycle, estimating the duration from the preparation for monitoring to obtaining the monitoring data. For out-of-hospital detections, the duration from the preparation to departure to return is accumulated; use the estimated duration as an additional simulation value, or detection accuracy, efficiency, implementation difficulty, etc. can also be used as additional simulation values;

[0067] Calculate the screening value of the corresponding candidate monitoring method according to the screening formula. The screening formula is:

[0068] SA = b1×CB + b2×FA;

[0069] In the formula: SA is the screening value; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 ≤ b2 ≤ 1; FA is the additional influence value;

[0070] Determine the target monitoring plan according to the screening value.

[0071] The data analysis module is used to analyze the status monitoring data of the patient to obtain status result data. The status result data includes the health stage, potential risks, and health management plan; and send the status result data to the user display module respectively.

[0072] In one embodiment, analyzing the status monitoring data of the patient can be based on existing methods;

[0073] Exemplarily, how to determine potential risks:

[0074] Data collection and preprocessing: Continuously monitor key indicators such as the foot temperature, humidity, and pressure distribution of patients. Conduct preprocessing tasks such as data cleaning and denoising to ensure the accuracy and reliability of the data.

[0075] Intelligent analysis: The platform uses advanced machine learning algorithms to analyze the preprocessed data.

[0076] The algorithm can identify abnormal patterns in the data. For example, a sudden increase in foot temperature may indicate blood circulation disorders, and an abnormal increase in humidity may predict the risk of infection, etc.

[0077] Risk assessment: Based on the analysis results of the algorithm, the platform will assess the current diabetic foot risk of the patient. The risk assessment may consider multiple factors such as the patient's medical history, age, gender, lifestyle habits, etc. to provide a more comprehensive risk assessment.

[0078] How to develop a health management plan:

[0079] Personalized recommendations: According to the patient's risk assessment results and historical data, the platform will generate a personalized health management plan. The plan may include suggestions such as adjusting diet, increasing exercise, improving sleep, and regularly checking the foot condition.

[0080] Real-time monitoring and feedback: The platform will continuously monitor the patient's data and adjust the health management plan in a timely manner according to the data changes. If abnormal data appears, the platform will issue an alarm in a timely manner to remind the patient to take corresponding measures.

[0081] Education and support: The platform will also provide educational materials related to diabetic foot to help patients understand the disease knowledge and improve their self-management ability. At the same time, the platform can also provide psychological support to help patients cope with the stress brought by the disease.

[0082] How to determine the health stage:

[0083] List all the health stages, mark the identification characteristics of each health stage, and perform feature matching based on the patient's status monitoring data to determine the health stage.

[0084] Example:

[0085] Suppose there is a diabetic patient who wears a smart sock to monitor the foot condition. One day, the smart sock detects that the foot temperature of the patient has increased abnormally and has lasted for some time. This data is transmitted to the cloud platform in real time, and the platform immediately analyzes the data.

[0086] Determine potential risks: The platform identifies that the abnormal increase in foot temperature may be related to blood circulation disorders, so the patient is marked as a high-risk group.

[0087] Formulate a health management plan: The platform generates a personalized health management plan, recommending that the patient rest immediately and elevate the feet to reduce swelling; at the same time, it is recommended that the patient seek medical attention as soon as possible for further examination and treatment.

[0088] Real-time monitoring and feedback: In the following days, the platform continuously monitors the patient's data and finds that the foot temperature gradually returns to normal. The platform timely adjusts the health management plan and recommends that the patient continue with appropriate exercise to promote blood circulation.

[0089] In one embodiment, the method for determining the health stage includes:

[0090] Preset corresponding stage recognition features for all health stages; establish a corresponding stage recognition model based on the obtained stage recognition features. The expression of the stage recognition model is:

[0091]

[0092] In the formula: (HZ, TP i ) is the input data, HZ is the status monitoring data; TP i represents the stage recognition feature of the corresponding health stage, i represents the corresponding health stage, i = 1, 2,..., n, n is the number of health stages; HZ → TP i means that the status monitoring data conforms to the stage recognition feature of the corresponding health stage; the output data is the stage recognition value DS(HZ, TP i ), and the stage recognition value is 1 or 0;

[0093] Analyze the status monitoring data through the stage recognition model to obtain the stage recognition value corresponding to the corresponding health stage, and determine the patient's health stage according to the stage recognition value.

[0094] The monitoring module is used to perform status monitoring on the patient according to the target monitoring plan, obtain corresponding status monitoring data, such as physiological parameters such as blood glucose, blood pressure, heart rate, body temperature, etc., and specific indicators such as foot skin temperature, humidity, blood circulation status, etc.; send the status monitoring data to the cloud computing platform.

[0095] In one embodiment, in order to ensure the patient's data monitoring and monitoring convenience, assist the user in monitoring management according to the target monitoring plan.

[0096] In one embodiment, to assist the user in monitoring management, the corresponding monitoring time requirements can be determined according to the target monitoring plan, such as interval time monitoring, interruption duration reminder, etc.; give auxiliary prompts to the user according to the monitoring time requirements.

[0097] In one embodiment, assisting the user in monitoring management according to the target monitoring plan further includes:

[0098] According to the target monitoring plan, it is determined whether it is necessary to go to places such as hospitals for examinations, which is regarded as whether it is necessary to make an appointment for off-site monitoring. Real-time judgment can be carried out by establishing an appointment judgment model. The expression of the appointment judgment model is:

[0099]

[0100] In the formula: S is the target monitoring plan; S meeting the appointment judgment requirements means that it is determined according to the target monitoring plan that it is necessary to make an appointment for off-site monitoring; the output data is the appointment judgment value YP(S), and the appointment judgment value is 1 or 0;

[0101] The target monitoring plan is analyzed through the appointment judgment model to obtain the corresponding appointment judgment value;

[0102] When the appointment judgment value is 0, no corresponding processing is performed;

[0103] When the appointment judgment value is 1, the appointment event information is identified according to the target monitoring plan. The appointment event information includes relevant information such as the monitoring time interval, hospital clinic, and examination items. Monitoring appointment processing is carried out according to the appointment event information, that is, intelligent medical appointment is carried out according to the appointment event information, and an appointment is made with the corresponding hospital according to the patient information authorized by the user. After being confirmed by the user or the patient, etc., the appointment is completed; and appointment reminder data is generated, that is, when to remind the patient to go for a medical examination.

[0104] The user display module is used for data display, receiving status result data, and displaying the status result data to the user.

[0105] The guidance module is used for guidance processing according to the guidance needs of the patient. Because during the period when the patient is outside the hospital, it is easy to have various needs for professional consultation and guidance. And when the patient has guidance needs, it is often impossible to obtain professional guidance in a timely manner, especially in some emergency situations, where the timeliness requirement for professional guidance is higher; therefore, guidance processing is carried out through the guidance module, including:

[0106] The platform party connects with various professionals related to diabetic foot, generally relevant doctor personnel, marked as guidance personnel, obtains the professional information of each guidance personnel. The professional information mainly includes the advantageous information of the guidance personnel regarding this disease, such as educational background, employment experience, professional ability, etc. The relevant information is integrated into the guidance personnel information; an information repository is established according to the guidance personnel information;

[0107] The platform party presets several status reference standards, that is, the platform party selects several representative patient statuses from various possible patients. For example, they are sorted from good to bad as 1 to 100, and 1, 10, 20, 30, 40, ……, 90, 100 are selected as reference standards. It can be set with reference to existing clustering algorithms, etc., and specifically set by the platform party. For example, the platform party organizes an expert group to set several status reference standards to help the guiding personnel quickly understand the corresponding situation of the patients, so that when encountering new patients, the guiding personnel cannot quickly understand the patient details; the status reference standards are displayed to the guiding personnel, and the guiding personnel need to be familiar with each status reference standard;

[0108] Determine the feature collection items according to each status reference standard; collect real-time features of the patient according to the feature collection items to obtain patient feature data, match the patient feature data with each status reference standard, determine the status reference standard to which the patient belongs, and label the patient with the corresponding status reference standard; matching can be performed through similarity;

[0109] When the user has a guiding need, generate patient condition data according to the patient's status result data and status monitoring data, create a data template according to the data required for the guiding personnel to make a diagnosis and guidance, and then collect the patient condition data according to the data template;

[0110] Match the guiding personnel information that meets the guiding needs from the information repository according to the guiding needs, and determine whether it meets the guiding needs according to whether it is online, idle, within the guiding scope, etc.; screen the guiding personnel who meet the guiding needs to determine several candidate guiding personnel; display the guiding personnel information of the candidate guiding personnel to the user, and the user determines the target guiding personnel; send the patient condition data and guiding needs to the target guiding personnel; the target guiding personnel conducts guiding processing on the patient.

[0111] In one embodiment, screening the guiding personnel who meet the guiding needs can be based on existing methods for screening and recommendation to obtain a preset number of candidate guiding personnel.

[0112] In one embodiment, the method for screening the guiding personnel who meet the guiding needs includes:

[0113] Obtain the evaluation data or scores of each user for the corresponding guiding personnel in real time, determine the scores of the guiding personnel, and for the evaluation data, use existing evaluation analysis algorithms to determine the corresponding scores; or a corresponding scoring system can be built in to dynamically determine the scores of the corresponding guiding personnel;

[0114] Obtain the number of times each guiding personnel has guided the patient;

[0115] Calculate the screening value of the guiding personnel according to the screening formula, and the screening formula is:

[0116] PU = b3 × PF + b4 × ln(CN + 1);

[0117] Where: PU is the screening value; b3 and b4 are both proportionality coefficients, and the value ranges are 0 < b3 ≤ 1, 0 ≤ b4 ≤ 1; PF is the score; CN is the number of guidance times;

[0118] Mark the instructors with a screening value greater than the threshold X1 as the to-be-selected instructors.

[0119] The above formulas are all calculated by removing the dimension and taking the numerical value. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained by a large amount of data simulation.

[0120] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A diabetes foot health management system based on cloud computing, characterized in that, It includes a cloud computing platform, a monitoring module, and a user display module; The cloud computing platform includes a monitoring and analysis module, a data analysis module, and a guidance module; The monitoring and analysis module is used to determine the target monitoring plan for the patient and send the target monitoring plan to the monitoring module; The data analysis module is used to analyze the status monitoring data of the patient to obtain status result data, and the status result data includes a health stage, potential risks, and a health management plan; Send the status result data to the user display module respectively; The monitoring module is used to perform status monitoring on the patient according to the target monitoring plan, obtain corresponding status monitoring data, and send the status monitoring data to the cloud computing platform; The user display module is used for data display, receives the status result data, and displays the status result data to the user; The guidance module is used to perform guidance processing according to the guidance needs of the patient.

2. The cloud computing-based diabetic foot health management system according to claim 1, characterized in that, The method for determining the target monitoring plan includes: Set up a monitoring parameter table, which is used to count the monitoring items required for diabetic foot monitoring and the monitoring requirement labels of the monitoring items for different health stages. The monitoring requirement labels include necessary labels, optional labels, and unnecessary labels; Identify the health stage of the patient, match the corresponding necessary monitoring items and optional monitoring items from the monitoring parameter table according to the health stage, display the necessary monitoring items and optional monitoring items to the user, and let the user determine each monitoring parameter item to be monitored; Analyze various candidate monitoring methods based on the monitoring parameter items, screen the candidate monitoring methods, and obtain the target monitoring plan.

3. The diabetes foot health management system based on cloud computing according to claim 2, characterized in that, The method for screening the candidate monitoring methods includes: Combine the candidate monitoring methods according to the monitoring parameter items to form several candidate monitoring plans; perform simulation analysis on the candidate monitoring plans to obtain the corresponding estimated cost and additional simulation values; Calculate the screening value of the candidate monitoring methods according to the screening formula. The screening formula is: SA = b1×CB + b2×FA; In the formula: SA is the screening value; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 ≤ b2 ≤ 1; FA is the additional influence value; Determine the target monitoring plan according to the screening value.

4. The cloud computing-based diabetic foot health management system according to claim 1, characterized in that, The method for determining the health stage includes: Preset corresponding stage identification features for all health stages; establish a corresponding stage identification model according to the stage identification features. The expression of the stage identification model is: Where: (HZ, TP i ) is the input data, HZ is the status monitoring data; TP i represents the stage identification feature of the corresponding health stage, i represents the corresponding health stage, i = 1, 2,..., n, n is the number of health stages; HZ → TP i indicates that the status monitoring data conforms to the stage identification feature of the corresponding health stage; the output data is the stage identification value DS(HZ, TP i ), and the stage identification value is 1 or 0; Analyze the status monitoring data through the stage identification model to obtain the stage identification value corresponding to the corresponding health stage, and determine the health stage of the patient according to the stage identification value.

5. The cloud computing-based diabetic foot health management system according to claim 1, wherein Assist the user in monitoring management according to the target monitoring plan.

6. The cloud computing-based diabetic foot health management system according to claim 5, wherein The method for assisting the user in monitoring management according to the target monitoring plan includes: Establish a reservation judgment model. The expression of the reservation judgment model is: In the formula: S is the target monitoring plan; the output data is the reservation judgment value YP(S), and the reservation judgment value is 1 or 0; Analyze the target monitoring plan through the reservation judgment model to obtain the corresponding reservation judgment value; When the reservation judgment value is 0, no corresponding processing is performed; When the appointment judgment value is 1, identify appointment event information according to the target monitoring plan, perform monitoring appointment processing according to the appointment event information, generate appointment prompt data, and perform prompt processing according to the appointment prompt data.

7. The cloud computing-based diabetic foot health management system according to claim 1, characterized in that, The working method of the guidance module includes: Establish an information repository for storing information of guidance personnel; preset several status reference standards by the platform party, and set feature collection items according to the status reference standards; Perform real-time feature collection on the patient according to the feature collection items to obtain patient feature data, match the patient feature data with the status reference standards, determine the status reference standard to which the patient belongs, and label the patient with the corresponding status reference standard; When the user has a guidance requirement, generate patient condition data based on the patient's status result data and status monitoring data; Match the guidance personnel information that meets the guidance requirements from the information repository; screen the guidance personnel to determine several candidate guidance personnel; display the guidance personnel information of the candidate guidance personnel to the user, and let the user determine the target guidance personnel; send the patient condition data and the guidance requirement to the target guidance personnel, and let the target guidance personnel conduct guidance processing on the patient.

8. The cloud computing-based diabetic foot health management system according to claim 7, characterized in that, The method for screening guidance personnel includes: Obtain the score of the guidance personnel in real time; identify the number of times the guidance personnel guides the patient; Calculate the screening value of the guidance personnel according to the screening formula, and the screening formula is: PU = b3 × PF + b4 × ln(CN + 1); In the formula: PU is the screening value; b3 and b4 are both proportionality coefficients, and the value ranges are 0 < b3 ≤ 1, 0 ≤ b4 ≤ 1; PF is the score; CN is the number of guidance times; Determine the candidate guidance personnel according to the screening value.

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