CN120203572A - A wearable diabetes intelligent health monitoring management device and system - Google Patents

Abstract

The present invention relates to a wearable diabetes intelligent health monitoring management device and system, which is intended to provide continuous, real-time blood sugar monitoring and personalized health management solutions for diabetic patients. The device includes a blood sugar sensor, a wireless communication module, a processing unit, a battery module and a wearing bracket, which measures blood sugar concentration in real time through non-invasive technology, and transmits the data to an intelligent device or a cloud platform through a wireless communication module. The processing unit performs denoising and filtering on the received blood sugar data, and uses a data analysis algorithm to generate personalized health feedback and suggestions based on the patient's historical health data, diet, exercise, drug use and other information. The system also has an abnormal blood sugar monitoring function. When the blood sugar level is abnormal, it automatically pushes an alarm and provides corresponding health suggestions, such as diet adjustment, exercise recommendation and drug use adjustment. The system supports remote data sharing, and patients and their doctors can perform remote monitoring and health management through smart devices.

Description

Wearable intelligent health monitoring management device and system for diabetes

Technical Field

The invention relates to the technical field of health care systems, in particular to a wearable intelligent health care management device and system for diabetes.

Background

Diabetes is one of the most affected chronic diseases worldwide at present, especially type 2 diabetes, and the incidence rate thereof tends to rise year by year due to changes in lifestyle and eating habits. Typical symptoms of diabetes are abnormally elevated blood glucose, which if not effectively controlled for a long period of time, may lead to various complications including retinopathy, nephropathy, nerve damage and the like, severely threatening the health and quality of life of the patient. Therefore, how to effectively monitor and manage the blood glucose level of diabetics becomes an important issue for global health management.

Currently, diabetes management is mainly dependent on the following ways:

Traditional glucose meter monitoring-a patient manually tests blood glucose concentration using a glucose meter, typically before or after a meal, with a single presentation of data. Traditional blood glucose meters rely on active testing by the patient, but it is difficult to achieve comprehensive and continuous monitoring of blood glucose changes as patients often forget or fall short of testing. And the traditional glucometer only provides instantaneous data, can not present the long-term change trend of blood sugar, and can not reflect the dynamic condition of blood sugar fluctuation in real time.

Continuous blood sugar monitoring system (CGM) the continuous blood sugar monitoring (CGM) system is the advanced blood sugar monitoring technology at present, can provide real-time blood sugar change trend, but at present CGM equipment still has certain limitation. First, CGM systems are expensive, burdensome to average patients, and especially in some developing countries, have low popularity. Second, CGM devices typically need to be mounted on the skin or subcutaneously, requiring the patient to receive invasive procedures, which to some extent affect the patient's wearing comfort and willingness to use. In addition, CGM devices have some drawbacks in terms of data accuracy, device maintenance, sensor replacement, and the like.

Along with the popularization of mobile Internet and smart phones, many diabetics begin to use health management application programs and intelligent devices, such as smart bracelets, smart watches and the like, and combine blood glucose monitoring and health management. However, these smart devices mostly rely on patient-independent input data and are generally only able to provide periodic health management advice, lacking real-time dynamic monitoring and personalized health interventions. The existing intelligent health management system is often not tightly combined with the real-time physiological state and behavior data (such as blood sugar fluctuation, diet, exercise quantity, medicine use and the like) of a patient, so that the accuracy and timeliness of system suggestion are poor.

The fragmentation of the health management system, namely the existing intelligent health management equipment and application are often respectively and independently operated, and the integration of data and the data sharing capability of a cross-platform are lacked. Patients often need to manually enter and monitor a number of different health data (e.g., diet records, exercise amount, blood glucose levels, drug use, etc.), without an effective correlation and feedback mechanism between these data. This makes personalized treatment and health management of diabetes more difficult.

While existing blood glucose monitoring devices and health management systems have advanced in some respects, there are a number of shortcomings, primarily represented by the following:

The real-time performance and the continuity of the data are insufficient, the traditional glucometer can only provide single blood glucose measurement and cannot monitor blood glucose fluctuation in real time, and the CGM system still has certain invasiveness although providing continuous monitoring, is not suitable for all patients, has higher equipment cost and is difficult to popularize.

Health management lacks personalization and intelligence-existing intelligent health management devices and applications mostly rely on autonomous input by patients, and lack real-time data feedback and intelligent analysis. Even if some devices have a data recording function, intelligent analysis on multiple factors such as blood sugar fluctuation, diet, exercise, medicines and the like is mostly lacking, and personalized health intervention suggestions cannot be provided according to specific situations of patients.

The cross-platform data integration is difficult, and most of the existing intelligent devices and application programs cannot realize cross-device and cross-platform data sharing and integration. Patients often need to switch between multiple applications, manually enter various health data, and cannot form a complete health record. The lack of data integration and sharing makes it difficult for patients and doctors to comprehensively assess the health of patients during the course of diagnosis.

The wearing comfort of the device and the compliance of the patient are poor, and although some advanced intelligent health monitoring devices exist, many devices are uncomfortable to wear, and especially CGM devices require skin puncture of the patient, which causes long-term wearing difficulty. Furthermore, the use and maintenance of parts of the device is complex and, due to the large or unsightly size of the device itself, patients may be unwilling to wear for a long period of time, affecting their compliance.

The existing equipment can only provide blood sugar monitoring, and lacks real-time feedback and personalized advice. Patients often need to rely on doctors to adjust treatment regimens based on test results, but often miss optimal intervention opportunities due to lag in remote communication and real-time data analysis.

In summary, the prior art has obvious shortcomings in blood glucose monitoring, health data management, personalized treatment scheme, patient compliance and the like, and a more intelligent, convenient and economical technical solution is urgently needed to improve the health management effect of diabetes and the life quality of patients.

Therefore, we propose a wearable intelligent health care management device and system for diabetes to solve the above problems.

Disclosure of Invention

The invention aims to solve the problems in the prior art in the background art and provides a wearable intelligent health monitoring management device for diabetes.

The above object of the present invention is achieved by:

A wearable intelligent health care management device for diabetes, comprising:

The blood glucose sensor is used for measuring the blood glucose concentration of diabetics in real time, the blood glucose sensor adopts a non-invasive sensing technology, blood glucose data are acquired through the surface of skin by the sensor, and the sensor is an electrochemical sensor or an optical sensor, so that the blood glucose level can be accurately and continuously monitored;

the wireless communication module is used for transmitting the blood glucose data measured by the blood glucose sensor to an external intelligent device or a cloud platform through wireless signals, and the wireless communication module adopts wireless communication technologies such as Bluetooth Low Energy (BLE), wi-Fi or NFC to perform data transmission, so that the real-time property and the remote synchronization of the data are realized;

a processing unit, configured to receive and process data transmitted by the blood glucose sensor, where the processing unit includes:

The data preprocessing module is used for removing noise and filtering blood glucose data so as to ensure the accuracy of the data;

A data analysis module for analyzing trends in blood glucose levels over time and generating personalized health management advice based on patient health profiles (including, but not limited to, historical blood glucose data, diet, exercise, drug use, etc.);

A health feedback module that automatically generates health feedback, such as diet, exercise and medication adjustment advice, or issues an alarm prompt when blood glucose levels are abnormal, based on the data analysis results;

the battery module is used for providing power for each component of the device, is a rechargeable lithium battery or other batteries suitable for low-power consumption equipment, can support continuous operation of the device and has long endurance time;

The wearing support is used for fixing the blood glucose sensor, the wireless communication module, the processing unit and the battery module on a patient, and the wearing support is an adjustable wrist strap, a waistband or a chest strap, so that the device is comfortable and firm to wear, and is suitable for daily use.

As a preferable technical scheme of the invention, the blood glucose sensor is an electrochemical sensor or an optical sensor, can be used for non-invasively measuring the blood glucose concentration in real time through the skin surface, and has higher measurement accuracy and stability.

As a preferred embodiment of the present invention, the data analysis module in the processing unit analyzes the blood glucose change of the patient using the following formula:

Wherein, the For the blood glucose level at time t,In order to initiate the blood glucose level,For the effect of diet on blood glucose levels,In order for exercise to have an effect on blood glucose levels,Is the effect of the drug on blood glucose levels.

As a preferable technical scheme of the invention, the data analysis module dynamically adjusts the influence weights of factors such as diet, exercise, medicine and the like of each patient according to the personalized health file, and the calculation formula is as follows:

Wherein, the For the type and amount of diet at the ith meal,In order for the intensity of the movement to be,In order to achieve the purpose of using the medicine,The weight coefficient of each factor on the blood sugar.

As a preferable technical scheme of the invention, the health feedback module pushes an alarm to the intelligent equipment of the user through the wireless communication module when abnormal blood glucose level is detected, and provides immediate health advice according to the blood glucose condition of the patient.

As a preferable technical scheme of the invention, the alarm reminds the user in a sound, vibration or notification pushing mode and displays the current blood sugar trend, historical data analysis and health adjustment suggestion through the mobile application program.

As the preferable technical scheme of the invention, the wireless communication module supports pairing and data synchronization with equipment such as a smart phone, a smart watch and a tablet personal computer, realizes real-time remote monitoring and management, and supports remote interaction and data sharing of a user and medical staff.

As the preferred technical scheme of the invention, the battery module is integrally designed and has an intelligent charging function, and can automatically monitor the electric quantity of the battery and remind a user of charging when the electric quantity is low.

The invention also provides an intelligent health management system, which comprises a wearable intelligent health monitoring management device for diabetes;

the mobile application program is used for receiving data from the blood glucose sensor and displaying real-time blood glucose information, and a user can feed back through the application program;

The cloud platform is used for storing and analyzing historical health data of a patient, generating a health file, providing personalized health suggestions for a user, and introducing machine learning and deepseek big models. According to basic vital signs, body height, body weight, waistline, constitution, blood sugar, diet, exercise, emotion and heart rate of a patient, the system is trained by a certain algorithm, and personalized guidance opinions are given according to real-time conditions of the patient.

As a preferred embodiment of the present invention, the data analysis module predicts a change in the patient's future blood glucose level using the following derivation formula:

Wherein, the For future time of dayThe predicted blood glucose level is determined to be,T is the predicted time interval, which is the rate of change of the current blood glucose level.

Compared with the prior art, the invention has the following beneficial effects:

The wearable intelligent health monitoring management device and system for diabetes provided by the invention have the advantages that the limitations of the traditional glucometer and the existing continuous blood sugar monitoring system are overcome by monitoring the blood sugar level in real time and integrating various health data analysis functions. The device can continuously monitor the blood sugar change of a patient in real time without manual testing of the patient, thereby remarkably improving the frequency and accuracy of blood sugar monitoring. The blood sugar data is analyzed through the intelligent algorithm, and the system can provide personalized health advice by combining factors such as diet, exercise, medicine use and the like of a patient, so that the patient can be helped to adjust the treatment scheme in time, the risk of hyperglycemia or hypoglycemia is avoided, and the occurrence of complications is effectively reduced.

In addition, the system provided by the invention has good user compliance and wearing comfort, and solves the problems of inconvenient wearing of patients, difficult maintenance of equipment and the like in the conventional equipment. The intelligent blood glucose monitoring system is connected with intelligent equipment (such as a smart phone and a smart watch) through the wireless communication module, so that a patient can check real-time blood glucose data and health feedback at any time, and the interaction is carried out through a mobile application program, so that continuous updating and timely feedback of the data are ensured. The comprehensive health management scheme not only improves the daily management efficiency of diabetics, but also provides more intelligent and convenient treatment support for the diabetics, and finally improves the life quality of the diabetics.

Drawings

In order to more clearly illustrate the invention or the technical solutions of the prior art, a brief description will be given below of the drawings used in the embodiments or the description of the prior art, it being obvious that the drawings in the following description are some embodiments of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.

Fig. 1 is a logic diagram of a wearable intelligent health monitoring management device for diabetes mellitus according to an embodiment of the present invention;

Fig. 2 is a system block diagram of an intelligent health management system in an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The following describes embodiments of the present invention in detail with reference to fig. 1 and 2.

The wearable intelligent health monitoring management device and system for diabetes realize real-time monitoring and intelligent health management of diabetics by integrating the functions of blood sugar monitoring, health data analysis, personalized feedback and the like. Embodiments will be described in detail below with reference to the technical content in the claims, and specific examples including technical implementation procedures, calculation procedures, and typical application scenarios are listed.

1. Overall system architecture

The wearable intelligent health monitoring management device for diabetes comprises the following main modules:

blood glucose sensor, which is to measure blood glucose concentration non-invasively through skin surface and monitor blood glucose level in real time by electrochemical sensor or optical sensor.

And the wireless communication module adopts a Bluetooth Low Energy (BLE) or Wi-Fi technology to transmit data to the intelligent equipment or the cloud platform, so that the synchronization and the remote monitoring of the data are realized.

And the processing unit is responsible for preprocessing, analyzing and generating health feedback. The system comprises a data preprocessing module, a data analysis module, a health feedback module and the like.

And the battery module is used for providing power for the device and supporting long-term use by adopting a high-efficiency and long-acting battery.

The wearing support is suitable for daily wearing of patients, and further components such as the blood glucose sensor and the like can stably operate.

2. Detailed description of the preferred embodiments

1. Blood sugar monitoring and data acquisition, wherein a blood sugar sensor detects blood sugar concentration in real time through a miniature sensor on the surface of skin. The working principle of the sensor can adopt electrochemical sensing or optical sensing technology. Electrochemical sensors detect blood glucose concentration through sweat or capillaries on the skin surface, while optical sensors measure blood glucose absorption at the skin layer by near infrared technology.

Whenever the sensor detects blood glucose data, the data is transmitted to the smart device or cloud platform through a wireless communication module (e.g., BLE module) for analysis by a subsequent processing unit.

2. And after the data preprocessing module in the processing unit receives the blood sugar data, the data is firstly denoised and filtered so as to eliminate noise possibly generated in the measuring process. For example, the raw blood glucose data is smoothed using a low pass filter to remove short term fluctuations and preserve long period trending changes.

Denoising formula:

Wherein, the In order to smooth the blood glucose data after it has been smoothed,For raw blood glucose measurements, N is the filter window size, and a time window of 5-10 minutes is typically selected.

3. The data analysis module is used for analyzing the historical blood sugar data, the diet, the movement, the medicine and other factors of the patient by using the following formulas:

Wherein, the For the blood glucose level at time t,In order to initiate the blood glucose level,For the effect of diet on blood glucose levels,In order for exercise to have an effect on blood glucose levels,Is the effect of the drug on blood glucose levels. The formula calculates the trend of the change of the blood glucose level by carrying out weighted summation on the feedback of the life habit, diet, exercise amount and medicine use condition of the patient.

4. Personalized health feedback, namely, through analysis of the data, the system automatically generates personalized health advice according to the change trend of the blood sugar level and the health file of the patient. For example, if the analysis results indicate that the patient's blood glucose level is continually getting higher for a certain period of time, the system may recommend adjusting the diet or increasing the amount of exercise, even reminding the patient to adjust the medication according to the doctor's prescription.

Health advice pushing formula:

Wherein, the For the type and amount of diet at the ith meal,In order for the intensity of the movement to be,In order to achieve the purpose of using the medicine,The weight coefficient of each factor on the blood sugar;

5. Abnormality monitoring and alarming: coefficient of influence of diet, exercise and drugs. By means of the formula, the system can calculate health feedback according to personalized data of the patient, and therefore advice is accurate and effective.

The health feedback module automatically sends an alarm when the blood glucose data is abnormal. The alarm is pushed to the patient through the mobile application program, and the relatives or doctors of the patient can be reminded through short messages, mails and the like. The system may prompt the patient if immediate medication adjustments or other actions are needed.

3. Examples

EXAMPLE 1 Standard diet and exercise management

The patient in this embodiment is a type 2 diabetes patient, and blood glucose monitoring is performed at ordinary times through the wearable diabetes intelligent health monitoring management device. The blood glucose level of a patient typically increases after a meal, especially after high-sugar food intake. The system automatically provides personalized diet and exercise adjustment advice for the patient by monitoring the blood sugar change of the patient in real time and analyzing by combining with factors such as diet and exercise.

And blood sugar data acquisition, namely after a patient wears the device, the blood sugar sensor monitors the blood sugar concentration of the patient in real time through an electrochemical sensing technology. When the patient meals, the device will automatically record the change in blood glucose level.

Assuming that the patient has consumed a meal of high sugar containing 50 grams of sugar, the blood glucose sensor records a postprandial blood glucose of 200mg/dL, approximately equal to 11.1mmol/L.

And data preprocessing, namely transmitting blood glucose data to the intelligent equipment through the wireless communication module.

The data preprocessing module performs noise removal and filtering on the original data, so that the stability and the accuracy of the data are further improved. For example, the data is smoothed using a moving average method, avoiding the influence of short-term fluctuations on the analysis result.

The postprandial blood glucose data for the patient were assumed to be: The filtered data is 。

Data analysis the data analysis module uses the formula:

Calculating a change in blood glucose, wherein: (the effect of diet on blood glucose, 50 grams of sugar on blood glucose is 40mg/dL, approximately equal to 2.22 mmol/L);

(assuming that the patient walks for 30 minutes, the effect of exercise on blood glucose is-15 mg/dL); (no drug is currently used by the patient). Based on the above data, the system calculated the trend of blood glucose level change of the patient after 1 hour of meal as follows:

And generating health feedback by the system according to the blood sugar change trend. Since it is predicted that 1 hour postprandial blood glucose reaches 255mg/dL, approximately equal to 14.16mmol/L, the normal range is significantly exceeded (the normal range is generally 80-140 mg/dL).

The system recommends the patient to perform more exercise (e.g., 40 minutes of walking) after a meal to help lower blood glucose levels;

the dietary structure is adjusted to reduce the food with higher sugar content, and the food with higher fiber is suggested.

Health advice pushing, namely pushing a notification through a smart phone by the system to remind a patient to take action. After the patient receives the notification, the advice is reviewed and a decision is made to increase the amount of motion.

Data update assuming that the patient walks 40 minutes as recommended, the post exercise blood glucose level improves, and the final 2 hour postprandial blood glucose level drops to 170mg/dL, approximately equal to 9.44mmol/L, the health advice push is updated to maintain current diet and exercise habits.

Results and effects the patient successfully adjusted the diet and exercise program according to the systematic advice, avoiding excessive postprandial blood glucose elevation. Through continuous monitoring and feedback, the patient can manage his diabetes more accurately, improving quality of life and reducing risk of long-term complications.

Example 2 drug use modulation and Low blood glucose monitoring

The patient in this example was a type 1 diabetic patient and insulin was used for glycemic control. Patients have recently taken more insulin because of less activity, resulting in an excessive decrease in blood glucose. This example demonstrates how an intelligent healthcare system monitors blood glucose changes, and timely pre-warns and helps patients adjust drug usage. Blood sugar data acquisition, namely, after a patient wears the device, the blood sugar sensor monitors the blood sugar concentration in real time through an optical sensing technology. Suppose that the patient had a rapid drop in blood glucose to 50mg/dL 1 hour after insulin administration, approximately equal to 2.77mmol/L. The data recorded by the blood glucose sensor is transmitted to the smart phone through the wireless communication module.

And the data preprocessing is to remove noise and filter blood sugar data due to the fact that blood sugar of a patient is fast to fall. Assume that the raw data is: (continuous decrease in blood glucose), the filtered data were: . The data analysis module calculates a trend of blood glucose changes and detects a hypoglycemic event. Based on historical blood glucose data, diet, exercise, etc., the system calculates:

wherein, the drug effect is: (insulin effect on blood glucose) the system calculates by equation that the current trend toward hypoglycemia persists, predicting that the patient's blood glucose will drop to 40mg/dL in 30 minutes, approximately equal to 2.22mmol/L, beyond the low blood glucose warning value.

And the data analysis and the hypoglycemia early warning are that the patient receives the hypoglycemia alarm through the intelligent equipment and immediately ingests the sugar-containing beverage according to the system suggestion. The smart device also displays the current blood glucose level and the recommended intake of the sugar component.

The health feedback generation, wherein the system recognizes the trend of hypoglycemia and automatically pushes the early warning information;

health advice pushing-prompting the patient to immediately ingest confectionary (e.g., sugar-containing beverages, juices, etc.);

the patient is reminded to reduce the insulin dosage or communicate with the doctor to adjust the medication.

And (3) updating data and adjusting the medicine, namely updating the health advice after the system receives feedback data of the patient, calculating new medicine usage amount and reminding the patient to monitor blood sugar regularly.

Assuming the patient reduced insulin dosage as recommended and monitored that blood glucose gradually returns to normal levels, the system continues to provide long-term monitoring and regulatory advice.

The result and effect are that through real-time data analysis and feedback of the intelligent health monitoring system, the patient can timely identify the risk of hypoglycemia and take measures, and serious consequences of hypoglycemia are avoided. Personalized drug adjustment of the system suggests helping patients reduce the risk of drug overuse and promote long-term health management.

Summarizing, the two embodiments show specific applications of the wearable diabetes intelligent health monitoring management device in daily life. Example 1 focuses on diet and exercise regulation, while example 2 demonstrates drug regulation and hypoglycemia monitoring. In each embodiment, the system helps diabetics effectively manage blood glucose, avoids health risks, and optimizes treatment regimens through real-time monitoring, data analysis, and personalized feedback.

It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present invention.

Claims (10)

1. Wearable intelligent health care management device of diabetes, characterized in that includes:

The blood glucose sensor is used for measuring the blood glucose concentration of diabetics in real time, the blood glucose sensor adopts a non-invasive sensing technology, blood glucose data are acquired through the surface of skin by the sensor, and the sensor is an electrochemical sensor or an optical sensor;

The wireless communication module is used for transmitting the blood glucose data measured by the blood glucose sensor to an external intelligent device or a cloud platform through wireless signals, and the wireless communication module adopts a Bluetooth low-power consumption, wi-Fi or NFC wireless communication technology for data transmission;

a processing unit, configured to receive and process data transmitted by the blood glucose sensor, where the processing unit includes:

the data preprocessing module is used for removing noise and filtering blood glucose data;

The data analysis module is used for analyzing the trend of the blood glucose level along with the change of time and generating personalized health management advice according to the health file of the patient;

A health feedback module that automatically generates health feedback, such as diet, exercise and medication adjustment advice, or issues an alarm prompt when blood glucose levels are abnormal, based on the data analysis results;

a battery module for providing power to the various components of the apparatus, the battery module being a rechargeable lithium battery or other battery suitable for use in low power devices;

the wearing support is used for fixing the blood glucose sensor, the wireless communication module, the processing unit and the battery module on a patient, and the wearing support is an adjustable wrist strap, a waistband or a chest strap.

2. The wearable diabetes intelligent health monitoring management device of claim 1, wherein the blood glucose sensor is an electrochemical sensor or an optical sensor, and the blood glucose concentration is measured non-invasively and in real time through the skin surface.

3. The wearable diabetes intelligent healthcare management device of claim 1, wherein the data analysis module in the processing unit analyzes the patient's blood glucose changes using the following formula:

Wherein, the For the blood glucose level at time t,In order to initiate the blood glucose level,For the effect of diet on blood glucose levels,In order for exercise to have an effect on blood glucose levels,Is the effect of the drug on blood glucose levels.

4. The wearable intelligent health monitoring and management device of claim 3, wherein the data analysis module dynamically adjusts the impact weights of the diet, exercise and drug factors of each patient according to the personalized health file, and the calculation formula is:

Wherein, the For the type and amount of diet at the ith meal,In order for the intensity of the movement to be,In order to achieve the purpose of using the medicine,The weight coefficient of each factor on the blood sugar.

5. The wearable diabetes intelligent health monitoring management device of claim 1, wherein the health feedback module pushes an alarm to a user's intelligent device via the wireless communication module when abnormal blood glucose levels are detected and provides immediate health advice based on the patient's blood glucose status.

6. The wearable diabetes intelligent health monitoring management device of claim 5, wherein the alarm alerts the user by means of sound, vibration or notification push, and displays current blood glucose trends, historical data analysis and health adjustment advice by mobile application.

7. The wearable diabetes intelligent health monitoring and management device according to claim 1, wherein the wireless communication module supports pairing and data synchronization with a smart phone, a smart watch and a tablet computer device, realizes real-time remote monitoring and management, and supports remote interaction and data sharing between a user and medical staff.

8. The wearable diabetes intelligent health monitoring and management device according to claim 1, wherein the battery module is of an integrated design and has an intelligent charging function, and can automatically monitor the battery power and remind a user of charging when the battery power is low.

9. An intelligent health management system comprising the wearable diabetes intelligent health monitoring management device of any one of claims 1 to 8, characterized in that;

the mobile application program is used for receiving data from the blood glucose sensor and displaying real-time blood glucose information, and a user can feed back through the application program;

the cloud platform is used for storing and analyzing historical health data of a patient, generating health files, providing personalized health suggestions for a user, introducing machine learning and deepseek big models, training according to certain algorithms according to basic vital signs, body weight and waistline, physique, blood sugar, diet, exercise, emotion and heart rate of the patient, and providing personalized guidance comments according to real-time conditions of the patient.

10. The intelligent health management system of claim 9, wherein the data analysis module predicts a change in the patient's future blood glucose level using the following derivation formula:

Wherein, the For future time of dayThe predicted blood glucose level is determined to be,T is the predicted time interval, which is the rate of change of the current blood glucose level.