Blood glucose management system based on artificial intelligence

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a blood glucose management system based on artificial intelligence. According to the system, blood glucose monitoring is reminded through the blood glucose monitoring terminal, a blood glucose curve is drawn every week, abnormal blood glucose conditions are judged for reminding and alarming, the diet terminal is used for guiding low-sugar diet recommendation, high-sugar food intake is avoided, the mastering degree of a patient and family members for food classification is improved, and the exercise terminal determines the exercise time and exercise amount of the patient according to the blood glucose value. Parameters are input into an intelligent system, the system converts and selects a motion mode, time and intensity, a drug treatment terminal calculates the insulin injection amount of a patient every day and every meal according to the blood glucose level and food intake, the insulin dosage is adjusted according to the calculated numerical values, blood glucose fluctuation is reduced, and the treatment effect is improved. The education and self-management terminal guides a patient to improve the cognitive degree of diabetes and provides personalized propaganda and education guidance for the patient, and the complication reminding terminal controls the blood sugar of the patient within a normal range, guides a good lifestyle of the patient and guides behavior specifications.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a blood sugar management system based on artificial intelligence. Background Art

[0002] In recent years, the incidence of diabetes has increased year by year. In its prevention and management, technology has been continuously innovated, such as continuous blood glucose monitoring devices CGM and artificial pancreas. However, the technology still only focuses on blood glucose monitoring and recording. Patients and their families are not familiar with diabetes-related knowledge, resulting in the inability to implement comprehensive diabetes management. Therefore, we will use AI as an intelligent auxiliary diagnosis and treatment tool to enter the chronic disease management of diabetes and propose a new management strategy. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] In view of the deficiencies in the prior art, the present invention provides a blood glucose management system based on artificial intelligence, which has the functions of reminding blood glucose monitoring point by point through a blood glucose monitoring terminal, interpreting the significance of each blood glucose measurement, drawing a blood glucose curve every week, calculating the blood glucose concentration Xtnd, judging abnormal blood glucose conditions and issuing reminder alarms, setting blood glucose control targets for patients with T1DM, T2DM and gestational diabetes, and transmitting the above information to a diet terminal, which is used to guide low-sugar diet recommendations, avoid high-sugar food intake, and improve the patient's and their family's mastery of food classification, daily reminders, daily uploading of recipes to identify food calories, and calculating the carbohydrate content Thhl, while using AI to assist in personalized recipe customization, guiding the patient's daily diet, and transmitting the above-derived data to an exercise terminal, which is used to determine the patient's exercise time and amount according to the blood glucose value, and calculate the patient's consumed calories Xhkl, input the parameters into the intelligent system, and the system converts and selects the exercise method, time and intensity, and transmits the derived data to the drug treatment terminal, the drug The treatment terminal is used to calculate the patient's daily basal insulin injection amount Jczs and the insulin injection amount Mczs for each meal according to the blood sugar level and food intake. The insulin dosage is adjusted according to the above calculated values, and the patient is given regular oral hypoglycemic drug treatment to reduce blood sugar fluctuations. The education and self-management terminal guides patients to improve their diabetes awareness based on the above calculated values, provides personalized education and guidance for patients, regulates patients' meals, reasonably adds meals, promotes patients' postprandial blood sugar stability, restricts patients' smoking and drinking, reasonably plans exercises, prevents patients from hypoglycemia, and generates a patient education management report and sends it to the complication reminder module. The complication reminder terminal controls the patient's blood sugar within the normal range based on the patient education management report, guides patients to a good lifestyle, and issues early warning for persistent high or low blood sugar, informs them of the dangers, guides behavioral norms, and introduces artificial intelligence to manage diabetes, popularizes diabetes-related knowledge to patients and their families, and implements comprehensive diabetes management, thereby solving the above problems.

[0005] (II) Technical solution

[0006] To achieve the above-mentioned object, the present invention provides the following technical solutions: a blood glucose management system based on artificial intelligence, comprising a blood glucose monitoring terminal, a diet terminal, an exercise terminal, a drug treatment terminal, an education and self-management terminal, and a complication reminder terminal;

[0007] The blood glucose monitoring terminal reminds the user to monitor blood glucose on time, interprets the significance of each blood glucose measurement, draws a blood glucose curve every week, calculates the blood glucose concentration Xtnd, determines abnormal blood glucose conditions and issues reminder alarms, sets blood glucose control targets for patients with T1DM, T2DM and gestational diabetes, and transmits the above information to the diet terminal;

[0008] The diet terminal is used to guide low-sugar diet recommendations, avoid high-sugar food intake, improve patients and their families' mastery of food classification, provide daily reminders, upload recipes daily to identify food calories, and calculate carbohydrate content Thhl. At the same time, AI assists in personalized recipe customization, guides patients' daily diet, and transmits the above-derived data to the exercise terminal;

[0009] The exercise terminal is used to determine the patient's exercise time and amount according to the blood sugar level, and calculate the patient's calorie consumption Xhkl, input the parameters into the intelligent system, the system converts and selects the exercise mode, time and intensity, and transmits the obtained data to the drug treatment terminal;

[0010] The drug treatment terminal is used to calculate the patient's daily basal insulin injection amount Jczs and the insulin injection amount per meal Xtnd according to the blood sugar level and food intake, adjust the insulin dosage according to the above calculated values ​​to reduce blood sugar fluctuations, and transmit the above obtained data to the education and self-management terminal;

[0011] The education and self-management terminal guides the patient to improve the degree of diabetes cognition according to the above calculated values, provides personalized education and guidance for the patient, regulates the patient's meals, reasonably adds meals, promotes the patient's blood sugar stability after meals, restricts the patient's smoking and drinking, reasonably plans exercise, performs hypoglycemia prevention treatment for the patient, and generates a patient education management report and sends it to the complication reminder module;

[0012] The complication reminder terminal controls the patient's blood sugar within a normal range according to the patient education management report, guides the patient to a good lifestyle, and issues early warning for persistent high or low blood sugar, informs the patient of the dangers, and guides behavioral norms.

[0013] Preferably, the blood glucose monitoring terminal reminds the user to monitor the blood glucose at a certain point and calculates the blood glucose concentration Xtnd. The calculation formula is as follows:

[0014]

[0015] In the formula, Xtnd represents the blood glucose concentration, x i+1 With x i Represents two adjacent time points on the blood glucose curve, y i With y i+1 Indicates that at the corresponding time point x i and x i+1 The function value at .

[0016] Preferably, the blood sugar monitoring terminal determines that the blood sugar is abnormal and issues an alarm, and the alarm conditions are set as follows:

[0017] When blood sugar is lower than 3.9mmol / L, the alarm is activated and the patient is reminded to eat through the loudspeaker.

[0018] Preferably, the blood glucose monitoring terminal sets a T1DM blood glucose control target as follows:

[0019] Normal adult HbA 1c The control target is less than 7.0;

[0020] The fasting and pre-meal blood sugar control targets for children and adolescents are between 4.0 and 7.0, and the post-meal blood sugar control targets are between 5.0 and 10.0.

[0021] HbA in the elderly 1c For those without complications and with a long life expectancy, the blood sugar control target is less than 7.5;

[0022] HbA in the elderly 1c For patients with mild to moderate complications, the blood sugar control target is less than 8.0;

[0023] HbA in the elderly 1c For patients with severe complications and poor general condition, the blood sugar control target should be less than 8.5.

[0024] Preferably, the blood glucose monitoring terminal sets a T2DM blood glucose control target as follows:

[0025] The fasting blood sugar control target is between 4.4 and 7.0;

[0026] The non-fasting blood sugar control target is less than 10.0;

[0027] Normal adult HbA 1c The control target is less than 7.0;

[0028] Those who are young, have a short course of disease, have no complications, have comorbidities, and have a low risk of hypoglycemia have HbA 1c The control target is less than 6.5;

[0029] HbA in patients with a long course of disease, a history of cardiovascular disease, or extremely high cardiovascular risk 1c The control target is less than 8.0;

[0030] HbA levels in elderly patients stratified by health status (good, moderate, poor) 1c The control target is between 7.5-8.5.

[0031] Preferably, the blood glucose monitoring terminal sets the blood glucose control target for patients with gestational diabetes as follows:

[0032] Pre-pregnancy HbA 1c The control target is less than 6.5, and the control target for insulin therapy is less than 7.0;

[0033] The target blood sugar level before meals before pregnancy is between 3.9 and 6.5.

[0034] The blood sugar control target after meals before pregnancy is less than 8.5;

[0035] The fasting blood sugar control target during pregnancy is less than 5.3;

[0036] The blood sugar control target one hour after a meal during pregnancy is less than 7.8;

[0037] The blood sugar control target two hours after a meal during pregnancy is less than 6.7.

[0038] Preferably, the diet terminal is used to guide low-sugar diet recommendations, avoid high-sugar food intake, improve patients and their families' mastery of food classification, provide daily reminders, upload recipes daily to identify food calories, and calculate carbohydrate content Thhl. The calculation formula is as follows:

[0039] Thhl=Swzl-Dbzz-Zfks-Sfzl-Hfkz

[0040] In the formula, Thhl represents the carbohydrate content, Swzl represents the total weight of food, Dbzz represents the total weight of protein, Zfks represents the total mass of fat, Sfzl represents the water content in food, and Hfkz represents the total amount of incombustible residue in food.

[0041] Preferably, the exercise terminal is used to determine the patient's exercise time and amount according to the blood sugar level, and calculate the patient's calorie consumption Xhkl, and the calculation formula is as follows:

[0042] Xhkl=Ydsj*METZ*Hztz

[0043] In the formula, Xhkl represents the calories consumed by the patient, Ydsj represents the patient's exercise time, METZ represents metabolic equivalent, and Hztz represents the patient's weight.

[0044] Preferably, the drug treatment terminal is used to calculate the patient's daily basal insulin injection amount Jczs according to the blood sugar level and food intake, and the calculation formula is as follows:

[0045] Jczs=Hztz*Ydxq

[0046] In the formula, Jczs represents the patient's daily basal insulin injection volume, Hztz represents the patient's weight, and Ydxq represents the insulin demand coefficient, which ranges from 0.5 to 1.0.

[0047] Preferably, the drug treatment terminal is used to calculate the insulin injection amount Mczs for each meal according to the blood sugar level and food intake, and the calculation formula is as follows:

[0048]

[0049] In the formula, Mczs represents the amount of insulin injected per meal, Thhl represents the carbohydrate content, Ydsb represents the insulin ratio, which is 10-15 grams per unit, Dqxt represents the patient's current blood sugar, Mbxt represents the patient's target blood sugar, and Ydsm represents insulin sensitivity, which is 30 mg per unit.

[0050] Compared with the prior art, the present invention provides a blood sugar management system based on artificial intelligence, which has the following beneficial effects:

[0051] The present invention uses a blood sugar monitoring terminal to remind blood sugar monitoring on point, interprets the significance of each blood sugar measurement, draws a blood sugar curve every week, calculates the blood sugar concentration Xtnd, determines blood sugar abnormalities and issues reminders and alarms, sets blood sugar control targets for patients with T1DM, T2DM and gestational diabetes, and transmits the above information to a diet terminal, which is used to guide low-sugar diet recommendations, avoid high-sugar food intake, and improve the patient's and their family's mastery of food classification, daily reminders, daily upload of recipes to identify food calories, and calculate carbohydrate content Thhl, while assisting in personalized recipe customization based on AI, guiding the patient's daily diet, and transmitting the above-derived data to an exercise terminal, which is used to determine the patient's exercise time and amount based on the blood sugar value, and calculate the patient's consumed calories Xhkl, input the parameters into an intelligent system, and the system converts and selects the exercise method, time and intensity, and transmits the derived data to a drug treatment terminal, which is used to determine the patient's exercise time and amount based on the blood sugar value, and calculates the patient's consumed calories Xhkl, inputs ... level, and food intake, calculate the patient's daily basal insulin injection volume Jczs and the insulin injection volume Mczs for each meal, adjust the insulin dosage according to the above calculated values, and make the patient take oral hypoglycemic drugs for regular treatment to reduce blood sugar fluctuations. The education and self-management terminal guides patients to improve their diabetes awareness based on the above calculated values, provides patients with personalized education and guidance, regulates patients' meals, reasonably adds meals, promotes patients' postprandial blood sugar stability, restricts patients' smoking and drinking, reasonably plans exercises, prevents patients from hypoglycemia, and generates a patient education management report and sends it to the complication reminder module. The complication reminder terminal controls the patient's blood sugar within the normal range based on the patient education management report, guides the patient to a good lifestyle, and warns patients of persistent high or low blood sugar, informs them of the dangers, guides behavioral norms, and manages diabetes by introducing artificial intelligence to popularize diabetes-related knowledge to patients and their families, and implements comprehensive diabetes management. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In view of the increasing incidence of diabetes, the technology in its prevention and management is constantly innovating, such as continuous blood glucose monitoring devices CGM and artificial pancreas. However, the technology still only focuses on blood glucose monitoring and recording, and patients and their families are not familiar with diabetes-related knowledge, resulting in the problem that the comprehensive management of diabetes cannot be implemented. Therefore, a blood glucose management system based on artificial intelligence is proposed. Please refer to Figure 1 ,The system includes blood glucose monitoring terminal, diet terminal, exercise terminal, drug treatment terminal, education and self-management terminal and complication reminder terminal;

[0055] The blood glucose monitoring terminal reminds you to monitor your blood glucose at every point, interprets the meaning of each blood glucose measurement, draws a blood glucose curve every week, calculates the blood glucose concentration Xtnd, determines abnormal blood glucose levels and issues reminders, and sets blood glucose control targets for patients with T1DM, T2DM, and gestational diabetes, including:

[0056] The formula for calculating blood glucose concentration is as follows:

[0057]

[0058] By analyzing the relationship between the patient's blood sugar response and diet and activity type, AI can develop a personalized blood sugar management plan to meet the unique needs of each patient. In the formula, Xtnd represents blood sugar concentration, x i+1 With x i Represents two adjacent time points on the blood glucose curve, y i With y i+1 Indicates that at the corresponding time point x i and x i+1 The system can combine data from a large number of other patients to find the most effective management strategy for a specific individual, thereby achieving more accurate blood sugar control. When blood sugar is lower than 3.9mmol / L, an alarm is activated and the patient is reminded to eat through a loudspeaker.

[0059] The blood sugar control target for T1DM is set as follows:

[0060] Normal adult HbA 1c The control target is less than 7.0;

[0061] The fasting and pre-meal blood sugar control targets for children and adolescents are between 4.0 and 7.0, and the post-meal blood sugar control targets are between 5.0 and 10.0.

[0062] HbA in the elderly 1c For those without complications and with a long life expectancy, the blood sugar control target is less than 7.5;

[0063] HbA in the elderly 1c For patients with mild to moderate complications, the blood sugar control target is less than 8.0;

[0064] HbA in the elderly 1c For patients with severe complications and poor general condition, the blood sugar control target is less than 8.5;

[0065] The blood sugar control target for T2DM is set as follows:

[0066] The fasting blood sugar control target is between 4.4 and 7.0;

[0067] The non-fasting blood sugar control target is less than 10.0;

[0068] Normal adult HbA 1c The control target is less than 7.0;

[0069] Those who are young, have a short course of disease, have no complications, have comorbidities, and have a low risk of hypoglycemia have HbA 1c The control target is less than 6.5;

[0070] HbA in patients with a long course of disease, a history of cardiovascular disease, or extremely high cardiovascular risk 1c The control target is less than 8.0;

[0071] HbA levels in elderly patients stratified by health status (good, moderate, poor) 1c The control target is between 7.5-8.5;

[0072] The blood sugar control target for patients with gestational diabetes is set as follows:

[0073] Pre-pregnancy HbA 1c The control target is less than 6.5, and the control target for insulin therapy is less than 7.0;

[0074] The target blood sugar level before meals before pregnancy is between 3.9 and 6.5.

[0075] The blood sugar control target after meals before pregnancy is less than 8.5;

[0076] The fasting blood sugar control target during pregnancy is less than 5.3;

[0077] The blood sugar control target one hour after a meal during pregnancy is less than 7.8;

[0078] The blood sugar control target two hours after a meal during pregnancy is less than 6.7;

[0079] Different groups of people, such as adults, children, the elderly, and pregnant women, have different physiology and pathology, so blood sugar control targets should be targeted to better meet individual health needs. Reasonable blood sugar control targets can help reduce the incidence of complications caused by diabetes, such as cardiovascular disease, kidney disease, and retinopathy, and protect the long-term health of patients. At the same time, controlling blood sugar within a reasonable range can reduce the discomfort caused by hypoglycemia and hyperglycemia, thereby improving the daily quality of life and happiness of patients.

[0080] The diet terminal is used to guide low-sugar diet recommendations, avoid high-sugar food intake, improve patients and their families' mastery of food classification, provide daily reminders, upload recipes daily to identify food calories, and use advanced computer vision and deep learning algorithms to scan food through the camera, automatically identify food types, and classify them as low-sugar, high-sugar or suitable for consumption. The system has a rich food database built in, including the nutritional ingredients, calories and carbohydrate content of various foods to ensure the accuracy of the recognition results and calculate the carbohydrate content Thhl. At the same time, AI assists in personalized recipes to guide patients' daily diets, and transmits the above-derived data to the exercise terminal;

[0081] The carbohydrate content is calculated as follows:

[0082] Thhl=Swzl-Dbzz-Zfks-Sfzl-Hfkz

[0083] By automatically calculating the carbohydrate content, patients can more accurately grasp the carbohydrate intake of each meal, thereby better controlling blood sugar levels. In the formula, Thhl represents the carbohydrate content, Swzl represents the total weight of food, Dbzz represents the total weight of protein, Zfks represents the total mass of fat, Sfzl represents the water content in food, and Hfkz represents the total amount of non-combustible residue in food. Through automated carbohydrate calculation, patients can manage their diet more effectively, increase their confidence in self-management, and thus improve their compliance with treatment plans.

[0084] The exercise terminal is used to determine the patient's exercise time and amount according to the blood sugar level, and calculate the patient's calories consumed Xhkl. The parameters are input into the intelligent system, and the system converts and selects the exercise method, time and intensity. According to the patient's blood sugar level and physical condition, the system recommends suitable exercise methods, such as aerobic exercise, strength training, flexibility training, etc., to ensure the diversity and fun of exercise. The system determines the best time and intensity of exercise based on real-time blood sugar data. For example, when the blood sugar level is high, the system may recommend moderate aerobic exercise, and when the blood sugar level is too low, it recommends light activity or rest. The exercise terminal transmits the calculated exercise data, such as exercise time, type, intensity and calorie consumption, to the drug treatment terminal in real time for comprehensive management by doctors and patients;

[0085] The formula for calculating the calories burned by the patient is as follows:

[0086] Xhkl=Ydsj*METZ*Hztz

[0087] The system can accurately calculate the calorie consumption of each type of exercise, helping patients understand the relationship between their energy consumption and intake, and supporting more effective energy management. In the formula, Xhkl represents the patient's calorie consumption, Ydsj represents the patient's exercise time, METZ represents metabolic equivalent, and Hztz represents the patient's weight. By monitoring calorie consumption, patients can better control their weight and prevent weight fluctuations caused by improper diet and exercise habits.

[0088] The drug treatment terminal is used to calculate the patient's daily basal insulin injection amount Jczs and the insulin injection amount per meal Mczs according to the blood sugar level and food intake. The insulin dosage is adjusted according to the above calculated values, and the patient is allowed to take oral hypoglycemic drugs for regular treatment to reduce blood sugar fluctuations, including:

[0089] The formula for calculating the patient's daily basal insulin injection volume is as follows:

[0090] Jczs=Hztz*Ydxq

[0091] By accurately calculating the basal insulin injection amount, the patient's blood sugar fluctuations can be effectively controlled to reduce the occurrence of hyperglycemia and hypoglycemia. In the formula, Jczs represents the patient's daily basal insulin injection amount, Hztz represents the patient's weight, and Ydxq represents the insulin demand coefficient, which ranges from 0.5 to 1.0. The system can share the patient's insulin injection amount and blood sugar data with the medical team, promote collaboration between doctors, nutritionists and other professionals, and develop a more comprehensive treatment plan;

[0092] The formula for calculating the amount of insulin to be injected per meal is as follows:

[0093]

[0094] By timely injecting appropriate insulin, patients can maintain stable blood sugar levels after meals and reduce fluctuations. In the formula, Mczs represents the amount of insulin injected per meal, Thhl represents the carbohydrate content, Ydsb represents the insulin ratio, which is 10-15 grams per unit, Dqxt represents the patient's current blood sugar, Mbxt represents the patient's target blood sugar, and Ydsm represents insulin sensitivity, which is 30 mg per unit;

[0095] The education and self-management terminal guides patients to improve their knowledge of diabetes based on the values ​​calculated above, provides personalized education and guidance for patients, regulates their meals, adds meals reasonably, promotes the stability of their blood sugar after meals, restricts their smoking and drinking, reasonably plans their exercise, prevents hypoglycemia, and generates a patient education and management report and sends it to the complication reminder module;

[0096] The complication reminder terminal controls the patient's blood sugar within the normal range based on the patient education management report, guides the patient to a good lifestyle, and issues early warning for persistent high or low blood sugar, informs the patient of the dangers, and guides behavioral norms.

[0097] The above-mentioned terminal is connected to the cloud server for cloud storage and processing of blood glucose monitoring information. Each smart terminal exchanges data with the corresponding terminal through the cloud server and can authorize other smart terminals to participate in the management of the blood glucose monitoring information. The blood glucose management application program running on the smart terminal also includes a configuration module, a communication module and a processing module.

[0098] Through the mutual cooperation of the above-mentioned terminals, artificial intelligence means are introduced to manage diabetes, popularize diabetes-related knowledge to patients and their families, and implement comprehensive management of diabetes.

[0099] 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. A blood sugar management system based on artificial intelligence, characterized in that: Including blood glucose monitoring terminal, diet terminal, exercise terminal, drug treatment terminal, education and self-management terminal and complication reminder terminal; The blood glucose monitoring terminal reminds the user to monitor blood glucose on time, interprets the significance of each blood glucose measurement, draws a blood glucose curve every week, calculates the blood glucose concentration Xtnd, determines abnormal blood glucose conditions and issues reminder alarms, sets blood glucose control targets for patients with T1DM, T2DM and gestational diabetes, and transmits the above information to the diet terminal; The diet terminal is used to guide low-sugar diet recommendations, avoid high-sugar food intake, improve patients and their families' mastery of food classification, provide daily reminders, upload recipes daily to identify food calories, and calculate carbohydrate content Thhl. At the same time, AI assists in personalized recipe customization, guides patients' daily diet, and transmits the above-derived data to the exercise terminal; The exercise terminal is used to determine the patient's exercise time and amount according to the blood sugar level, and calculate the patient's calorie consumption Xhkl, input the parameters into the intelligent system, the system converts and selects the exercise mode, time and intensity, and transmits the obtained data to the drug treatment terminal; The drug treatment terminal is used to calculate the patient's daily basal insulin injection amount Jczs and the insulin injection amount Mczs for each meal according to the blood sugar level and food intake, adjust the insulin dosage according to the above calculated values, reduce blood sugar fluctuations, and transmit the above obtained data to the education and self-management terminal; The education and self-management terminal guides the patient to improve the degree of diabetes cognition according to the above calculated values, provides personalized education and guidance for the patient, regulates the patient's meals, reasonably adds meals, promotes the patient's blood sugar stability after meals, restricts the patient's smoking and drinking, reasonably plans exercise, performs hypoglycemia prevention treatment for the patient, and generates a patient education management report and sends it to the complication reminder module; The complication reminder terminal controls the patient's blood sugar within a normal range according to the patient education management report, guides the patient to a good lifestyle, and issues early warning for persistent high or low blood sugar, informs the patient of the dangers, and guides behavioral norms.

2. The blood glucose management system based on artificial intelligence according to claim 1, characterized in that: The blood glucose monitoring terminal reminds the user to monitor the blood glucose at the designated point and calculates the blood glucose concentration Xtnd. The calculation formula is as follows: In the formula, Xtnd represents the blood glucose concentration, x i+1 With x i Represents two adjacent time points on the blood glucose curve, y i With y i+1 Indicates that at the corresponding time point x i and x i+1 The function value at .

3. The blood glucose management system based on artificial intelligence according to claim 2, characterized in that: The blood sugar monitoring terminal determines that the blood sugar is abnormal and issues an alarm. The alarm conditions are set as follows: When blood sugar is lower than 3.9mmol / L, the alarm is activated and the patient is reminded to eat through the loudspeaker.

4. The blood glucose management system based on artificial intelligence according to claim 3, characterized in that: The blood glucose monitoring terminal sets the T1DM blood glucose control target as follows: Normal adult HbA 1c The control target is less than 7.0; The fasting and pre-meal blood sugar control targets for children and adolescents are between 4.0 and 7.0, and the post-meal blood sugar control targets are between 5.0 and 10.

0. HbA in the elderly 1c For those without complications and with a long life expectancy, the blood sugar control target is less than 7.5; HbA in the elderly 1c For patients with mild to moderate complications, the blood sugar control target is less than 8.0; HbA in the elderly 1c For patients with severe complications and poor general condition, the blood sugar control target should be less than 8.

5.

5. The blood glucose management system based on artificial intelligence according to claim 4, characterized in that: The blood glucose monitoring terminal sets the T2DM blood glucose control target as follows: The fasting blood sugar control target is between 4.4 and 7.0; The non-fasting blood sugar control target is less than 10.0; Normal adult HbA 1c The control target is less than 7.0; Those who are young, have a short course of disease, have no complications, have comorbidities, and have a low risk of hypoglycemia have HbA 1c The control target is less than 6.5; HbA in patients with a long course of disease, a history of cardiovascular disease, or extremely high cardiovascular risk 1c The control target is less than 8.0; HbA levels in elderly patients stratified by health status (good, moderate, poor) 1c The control target is between 7.5-8.

5.

6. The blood glucose management system based on artificial intelligence according to claim 5, characterized in that: The blood glucose monitoring terminal sets the blood glucose control target for patients with gestational diabetes as follows: Pre-pregnancy HbA 1c The control target is less than 6.5, and the control target for insulin therapy is less than 7.0; The target blood sugar level before meals before pregnancy is between 3.9 and 6.

5. The blood sugar control target after meals before pregnancy is less than 8.5; The fasting blood sugar control target during pregnancy is less than 5.3; The blood sugar control target one hour after a meal during pregnancy is less than 7.8; The blood sugar control target two hours after a meal during pregnancy is less than 6.

7.

7. The artificial intelligence-based blood sugar management system according to claim 6, characterized in that: The diet terminal is used to guide low-sugar diet recommendations, avoid high-sugar food intake, improve patients and their families' mastery of food classification, provide daily reminders, upload recipes daily to identify food calories, and calculate carbohydrate content Thhl. The calculation formula is as follows: Thhl=Swzl-Dbzz-Zfks-Sfzl-Hfkz In the formula, Thhl represents the carbohydrate content, Swzl represents the total weight of food, Dbzz represents the total weight of protein, Zfks represents the total mass of fat, Sfzl represents the water content in food, and Hfkz represents the total amount of incombustible residue in food.

8. The artificial intelligence-based blood sugar management system according to claim 7, characterized in that: The exercise terminal is used to determine the patient's exercise time and amount according to the blood sugar level, and calculate the patient's calorie consumption Xhkl, and the calculation formula is as follows: Xhkl=Ydsj*METZ*Hztz In the formula, Xhkl represents the calories consumed by the patient, Ydsj represents the patient's exercise time, METZ represents metabolic equivalent, and Hztz represents the patient's weight.

9. The artificial intelligence-based blood sugar management system according to claim 8, characterized in that: The drug treatment terminal is used to calculate the patient's daily basal insulin injection amount Jczs according to the blood sugar level and food intake. The calculation formula is as follows: Jczs=Hztz*Ydxq In the formula, Jczs represents the patient's daily basal insulin injection volume, Hztz represents the patient's weight, and Ydxq represents the insulin demand coefficient, which ranges from 0.5 to 1.

0.

10. The artificial intelligence-based blood sugar management system according to claim 9, characterized in that: The drug treatment terminal is used to calculate the insulin injection amount Mczs for each meal according to the blood sugar level and food intake. The calculation formula is as follows: In the formula, Mczs represents the amount of insulin injected per meal, Thhl represents the carbohydrate content, Ydsb represents the insulin ratio, which is 10-15 grams per unit, Dqxt represents the patient's current blood sugar, Mbxt represents the patient's target blood sugar, and Ydsm represents insulin sensitivity, which is 30 mg per unit.

Images