Blood glucose and body weight collaborative management system and method based on dynamic periodic glucose interruption intervention

Abstract

The invention relates to the technical field of health management, in particular to a blood glucose and weight collaborative management method based on dynamic periodic glucose interruption intervention, which comprises the following steps: acquiring blood glucose data and weight data of a user; based on a comparison result of the blood glucose data and a personalized threshold value, dynamically triggering a high-strength sugar breaking period or a maintenance low-sugar period; performing extremely low-carbon water diet intervention in the sugar break period, and performing moderate low-carbon water diet intervention in the low-sugar period; and adjusting intervention parameters of the next period according to the weight change trend. According to the blood glucose and body weight collaborative management system and method based on dynamic periodic glucose interruption intervention, a glucose interruption-low glucose periodic alternating mechanism is created, metabolic conversion is induced by using a glucose interruption period, metabolic flexibility is consolidated and improved by using a low glucose period, and individual differences are adapted based on dynamic stage switching of a personalized blood glucose threshold value; through hardware cooperation, blood sugar and weight double-index real-time correlation analysis is realized, and personalized scheme making, special dietary food intelligent recommendation, real-time data monitoring and dynamic adjustment are realized.

Description

Technical Field

[0001] This invention relates to the field of health management technology, specifically to a blood glucose and weight co-management system and method based on dynamic periodic glucose withdrawal intervention. Background Technology

[0002] Coordinated management of blood glucose and weight is a core strategy for metabolic health management in individuals with prediabetes, type 2 diabetes mellitus (T2DM), and obesity. Its significance lies not only in improving blood glucose and weight but also in reducing cardiovascular risk, delaying complications, and improving quality of life. While existing guidelines and technologies (such as dynamic periodic glucose restriction and digital therapies) provide new pathways for coordinated management, patient adherence, integration of healthcare resources, and management of special populations remain pressing challenges. In the future, precision medicine, digitalization, and multidisciplinary collaboration are needed to drive the transformation of coordinated management from experience-based medicine to precision medicine, achieving long-term improvements in metabolic health.

[0003] Current blood glucose and weight management methods have the following shortcomings:

[0004] 1) Existing management methods mostly rely on single dietary control (such as continuous low sugar / low carb) or drugs, which have problems such as poor compliance, unstable effects, ignoring individual differences, and lack of dynamic adjustment, and are prone to decreased metabolic adaptation, stagnation or rebound of effects;

[0005] 2) At the same time, there is a lack of real-time collaborative analysis of blood glucose and weight data, and the intervention strategy is static and cannot be dynamically adapted to individual differences;

[0006] 3) In particular, special dietary foods are widely used in health management, but they are usually used as independent nutritional supplements and are not deeply integrated with personalized metabolic intervention cycles and real-time health data.

[0007] 4) Existing health management apps mainly provide data recording and simple suggestions, lacking the ability to generate personalized plans based on professional metabolic intervention models (such as the sugar-low sugar cycle), especially lacking intelligent matching and dynamic recommendation mechanisms with special dietary food libraries, and unable to form a closed-loop regulatory process of monitoring-analysis-intervention (including precision nutrition)-feedback.

[0008] Meanwhile, most existing patented technologies focus on a single indicator (blood sugar or weight only) or static diet plans, without involving the periodic alternation mechanism of high-intensity sugar cut-off and maintenance low sugar, resulting in insufficient intelligence and a lack of threshold-driven stage switching logic based on real-time data.

[0009] Therefore, based on the aforementioned technical shortcomings, a blood glucose and weight co-management system and method based on dynamic periodic glucose withdrawal intervention is proposed, which is particularly suitable for metabolic health management of patients with prediabetes, type II diabetes and obese individuals. Summary of the Invention

[0010] (a) Technical problems to be solved

[0011] To address the shortcomings of existing technologies, this invention provides a blood glucose and weight collaborative management system and method based on dynamic periodic glucose withdrawal intervention. It has the advantages of deeply integrating periodic glucose withdrawal, low-glucose metabolic intervention methods, a dedicated dietary food library, and an intelligent digital management platform. This solves the problems in the existing blood glucose and weight management methods mentioned above, which only focus on diet and medication control, lack collaborative analysis and intervention of blood glucose and weight data, and cannot generate personalized plans and dynamic recommendations based on professional metabolic intervention models.

[0012] (II) Technical Solution

[0013] To achieve the goal of deeply integrating the aforementioned periodic glucose deprivation-low glucose metabolism intervention method, dedicated dietary food library, and intelligent digital management platform technology, this invention provides the following technical solution: a method for coordinated blood glucose and weight management based on dynamic periodic glucose deprivation intervention, comprising the following specific steps:

[0014] S1. Obtain user's blood glucose and weight data;

[0015] S2. Based on the comparison results of blood glucose data and personalized thresholds, dynamically trigger high-intensity glucose withdrawal periods or maintenance low-glucose periods;

[0016] S3. Implement a very low-carbohydrate diet intervention during the sugar-free period and a moderately low-carbohydrate diet intervention during the low-carbohydrate period;

[0017] S4. Adjust the intervention parameters for the next cycle based on the trend of weight change.

[0018] A blood glucose and weight co-management system based on dynamic periodic glucose withdrawal intervention includes a mobile device APP as the user terminal module for data input, receiving instructions, and viewing reports;

[0019] The data acquisition and storage module is used to collect basic user data and dynamic monitoring data, and to store historical data and intervention records;

[0020] Special dietary food database, which categorizes and stores information on special dietary foods with scientific formulas and key parameters labeled;

[0021] The data analysis module is used to calculate the correlation between blood glucose variability and body weight.

[0022] The cycle decision engine module switches between sugar-free and low-sugar periods based on set personalized thresholds;

[0023] The personalized push module outputs corresponding diet and exercise plans based on different stages;

[0024] The monitoring and early warning module is used for real-time analysis and control effect evaluation, enabling risk warning and dynamic intervention and adjustment;

[0025] The user interaction module provides special dietary food suggestions and monitoring reminders, outputs visual reports, and allows user feedback.

[0026] Preferably, in the data acquisition and storage module, the user's basic data includes age, gender, height, weight, BMI, type of diabetes history, medication history, initial blood glucose level (fasting and postprandial), and control targets (blood glucose target and weight loss target).

[0027] The dynamic monitoring data includes periodic blood glucose levels (fasting and postprandial specific time points), daily weight, activity level (steps and duration of exercise type), subjective feedback (hunger, energy and sleep), and special dietary food intake records (type, quantity and time).

[0028] Preferably, the special dietary food database stores special dietary foods for the sugar-free period and special dietary foods for the low-sugar period separately. The labeled parameters include detailed labeling of each food's net carbohydrate content, fat content, protein content, dietary fiber content, energy value, key nutrients (electrolytes Na / K / Mg, vitamins, specific functional components such as chromium and alpha-lipoic acid), and glycemic index (GI) prediction indicators.

[0029] Preferably, the cycle decision engine generates a personalized plan based on a preset metabolic intervention model and rule base. The personalized threshold is dynamically set according to the user's diabetes type (pre-diabetes and type II), specifically including:

[0030] 1) Use the collected user basic data and dynamic monitoring data as model input;

[0031] 2) The model assesses the user's current metabolic status and risk based on the input data and determines the intervention cycle structure, including dynamically generating the initial number of days in the glucose-free period (D1), the number of days in the low-glucose period (D2), and the switching logic based on the blood glucose target value and the rate of weight change.

[0032] 3) Set the nutritional goals as follows: calculate the daily upper limit of net carbohydrates, protein and fat targets during the glucose-free period, and calculate the daily net carbohydrate target range, protein and fat targets during the low-glucose period; set the criteria for determining blood glucose stability at the end of the glucose-free period as: blood glucose level ≤ target threshold ± 0.5 mmol / L for 48 consecutive hours;

[0033] 4) Set blood sugar and weight control target ranges, and output a personalized periodic intervention plan in calendar view. Daily nutritional goals include net carbohydrates, protein, fat and energy.

[0034] Preferably, in the personalized push module, the current intervention stage (sugar-free period and low-sugar period), daily nutritional goals, user preferences, and historical feedback are used as input data for the special dietary food recommendation engine, and the data processing process is as follows:

[0035] 1) Based on the current stage, identify the corresponding categories in the special dietary food database (sugar-free period food database and low-sugar period food database);

[0036] 2) Based on the user's daily nutritional goal of limiting net carbohydrates, select special dietary foods that meet the nutritional parameter requirements from the locked categories;

[0037] 3) Sort and recommend based on user feedback (including taste preferences and satiety ratings), and calculate recommended intake to meet nutritional goals;

[0038] 4) Output: A list of recommended special meals (including pictures, names and reasons for recommendation) to be pushed to the user, along with the recommended serving size for each meal on that day;

[0039] 5) At the same time, provide purchase links for special dietary foods or interfaces for scheduled delivery services.

[0040] Preferably, the monitoring and early warning module continuously analyzes the input blood glucose, weight, activity and special dietary food intake data, and tracks blood glucose trends (stability and target achievement rate), weight change trends and periodic target achievement.

[0041] Identifying the risk of persistent hypoglycemia, abnormally high blood glucose, and weight plateaus, and setting dynamic intervention and adjustment steps includes:

[0042] 1) Triggering conditions include early warning signals, deviations from expected results, or switching according to planned cycles;

[0043] 2) Set the adjustment content as follows:

[0044] a. Adjustments to the intervention program: Modify the ratio of sugar-free and low-sugar days, switch the timing, and adjust daily nutritional goals, including tightening or relaxing net carbohydrate restrictions;

[0045] b. Adjustment of special dietary food recommendations: Based on changes in nutritional goals and the adjusted plan for the current stage, update the subsequent special dietary food recommendations in real time.

[0046] Preferably, the user interaction module provides a guide to the consumption of special dietary foods and suggestions for pairing them, and sends reminders for monitoring blood glucose, weight, taking special dietary foods and medications, and exercise records. It also outputs a visual report that shows blood glucose and weight change curves, cycle execution status, and correlation analysis between special dietary food intake and key indicators, in order to enhance user understanding and compliance.

[0047] It also provides a user feedback portal to showcase evaluations of the taste and effectiveness of special dietary foods, while connecting with community medical staff to enable remote data monitoring, abnormal intervention, and online consultation.

[0048] (III) Beneficial Effects

[0049] Compared with the prior art, the present invention provides a blood glucose and weight synergistic management system and method based on dynamic periodic glucose withdrawal intervention, which has the following beneficial effects:

[0050] 1. This blood glucose and weight co-management system and method based on dynamic periodic glucose deprivation intervention creates a periodic alternation mechanism of glucose deprivation and low glucose. It uses the glucose deprivation period to induce metabolic transformation and the low glucose period to consolidate and improve metabolic flexibility, thus breaking through the bottleneck of a single diet pattern. At the same time, it adapts to different individual differences based on the dynamic phase switching of personalized blood glucose thresholds and accurately meets the nutritional needs of different intervention stages through special dietary foods, ensuring safety and compliance.

[0051] 2. This blood glucose and weight co-management system and method based on dynamic periodic glucose withdrawal intervention achieves real-time correlation analysis of blood glucose and weight through hardware collaboration, and builds an intelligent decision engine to automatically trigger periodic switching. With the help of a digital platform, it realizes personalized plan formulation, intelligent recommendation of special dietary foods, real-time data monitoring and dynamic adjustment, reduces manual intervention and forms a management closed loop, and ultimately achieves the control goals of long-term stable blood glucose control and healthy weight loss. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the blood glucose and weight collaborative management system architecture of the present invention;

[0053] Figure 2 This is a flowchart of the periodic intervention of blood glucose according to the present invention;

[0054] Figure 3 for Figure 2 The first part of the diagram;

[0055] Figure 4 for Figure 2 The second part of the diagram;

[0056] Figure 5 for Figure 2 The third part of the diagram;

[0057] Figure 6 for Figure 2 The fourth part of the diagram;

[0058] Figure 7 This is a schematic table illustrating the changes in blood glucose levels during the second glucose withdrawal period for patient A, as presented in this invention.

[0059] Figure 8This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the second glucose withdrawal period for patient A according to the present invention.

[0060] Figure 9 This is a schematic table illustrating the blood glucose changes in patient A during the second hypoglycemic episode of this invention;

[0061] Figure 10 This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the second hypoglycemic episode in patient A according to the present invention.

[0062] Figure 11 This is a schematic table illustrating the changes in blood glucose levels during the third glucose withdrawal period for patient A, as presented in this invention.

[0063] Figure 12 This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the third glucose withdrawal period for patient A according to the present invention.

[0064] Figure 13 This is a schematic table illustrating the blood glucose changes of patient A during the third hypoglycemic episode of the present invention;

[0065] Figure 14 This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the third hypoglycemic episode in patient A according to the present invention.

[0066] Figure 15 This is a schematic table illustrating the blood glucose changes of patient A during the fourth glucose withdrawal period according to the present invention;

[0067] Figure 16 This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the fourth glucose withdrawal period for patient A according to the present invention.

[0068] Figure 17 This is a schematic table illustrating the blood glucose changes of patient A during the fourth hypoglycemic episode according to the present invention;

[0069] Figure 18 This is a schematic diagram illustrating the coordinated changes in blood glucose and body weight during the fourth hypoglycemic episode in patient A according to the present invention.

[0070] Figure 19 This is a schematic table illustrating the blood glucose changes of patient A during the fifth glucose withdrawal period according to the present invention;

[0071] Figure 20 This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the fifth glucose withdrawal period for patient A according to the present invention.

[0072] Figure 21 This is a schematic table illustrating the blood glucose changes of patient B during the second glucose withdrawal period according to the present invention;

[0073] Figure 22 This is a schematic diagram illustrating the coordinated changes in blood glucose and body weight during the second glucose withdrawal period for patient B according to the present invention.

[0074] Figure 23 This is a schematic table illustrating the blood glucose changes in patient B during the second hypoglycemic episode of this invention;

[0075] Figure 24 This is a schematic diagram illustrating the coordinated changes in blood glucose and body weight during the second hypoglycemic episode in patient B according to the present invention.

[0076] Figure 25 This is a schematic table illustrating the blood glucose changes of patient B during the third glucose withdrawal period according to the present invention;

[0077] Figure 26 This is a schematic diagram illustrating the coordinated changes in blood glucose and body weight during the third glucose withdrawal period for patient B according to the present invention.

[0078] Figure 27 This is a schematic table illustrating the blood glucose changes in patient B during the third hypoglycemic episode of the present invention.

[0079] Figure 28 This is a schematic diagram illustrating the coordinated changes in blood glucose and weight during the third hypoglycemic episode in patient B according to the present invention. Detailed Implementation

[0080] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments and accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] Example 1

[0082] In this embodiment, a dynamic periodic blood glucose intervention mechanism is introduced into the blood glucose and weight co-management method. This method includes two core phases, which are performed cyclically, including:

[0083] 1) Sugar withdrawal period

[0084] Duration: 3 days.

[0085] Objective: To rapidly reduce glycemic load and initiate fat metabolism.

[0086] Diet: Daily intake of very low carbohydrates ≤20g, with energy sources mainly consisting of special dietary foods (including black-striped snake and ginseng dendrobium soup or cobra and ginseng dendrobium soup), water, and necessary egg white supplements.

[0087] Monitoring: Monitor fasting blood glucose and blood glucose 2 hours after each meal at least daily, and monitor weight daily as well.

[0088] 2) Low sugar period

[0089] Duration: 7 to 14 days, with an initial default of 10 days. The duration of subsequent cycles will be dynamically adjusted based on the effectiveness of the sugar-free period.

[0090] Objectives: Maintain effectiveness, explore individual carbohydrate tolerance thresholds, and improve adherence.

[0091] Diet: Daily carbohydrate intake is set at 20g-100g, and a balanced diet is encouraged. Special dietary products recommended by the platform can be used as part of the meals.

[0092] Monitoring: Daily monitoring of fasting blood glucose and representative 2-hour postprandial blood glucose.

[0093] Cyclic Logic: The sugar-free period and the low-sugar period alternate sequentially and are carried out in a cycle (3 days of sugar-free → 10 days of low-sugar → 3 days of sugar-free → 10 days of low-sugar → ...) until the preset number of cycles or individualized health goals are reached.

[0094] Build data-driven, dynamically adjusting rules. The system automatically provides suggestions based on these rules, including:

[0095] Adjusting the duration of the low-glucose period: If the average blood glucose level drops significantly and the weight decreases steadily during the glucose-free period, the next low-glucose period can be maintained or extended for 1-2 days; if the effect is not good or there is a rebound, the low-glucose period can be shortened to 7 days.

[0096] Carbohydrate threshold exploration: During a low-glucose period, the carbohydrate intake of the next meal or the following day is fine-tuned based on postprandial blood glucose fluctuations (with a target of: 2-hour postprandial blood glucose <7.8mmol / L) to gradually find the individual's maximum tolerance threshold.

[0097] Safety alert: Set blood glucose safety thresholds (lower limit <4.0 mmol / L, upper limit fasting >7.0 mmol / L, postprandial >10.0~13.0 mmol / L). Once triggered, the system will immediately send an alert to the user and the associated medical staff and provide intervention suggestions.

[0098] Establish a standardized implementation and monitoring system, including:

[0099] 1) Dietary guidelines: Provide detailed food lists, portion size guidelines, and a list of foods to avoid (especially high-GI foods and added sugars) for the sugar-free and low-sugar periods.

[0100] 2) Requirements for high-frequency physiological indicator monitoring:

[0101] a. During the glucose withdrawal period: Monitor fasting blood glucose and blood glucose 2 hours after each meal at least daily, and add monitoring before bedtime or before meals if necessary;

[0102] b. Low glucose period: Monitor fasting blood glucose and blood glucose at least 1-2 times a day, 2 hours after a representative meal (choose the meal with the highest carbohydrate intake).

[0103] c. Daily or every other day weight monitoring.

[0104] 3) Regular health assessments: Before the intervention begins and after each complete cycle (glucose-free + low-glucose), a basic physical examination (including weight, BMI, waist circumference) and blood biochemistry tests (including blood glucose profile, HbA1c, blood lipids, liver and kidney function, uric acid, electrolytes - preferred baseline) are conducted.

[0105] Example 2

[0106] In this embodiment, based on research data from a community hospital, subject A was selected and underwent three cycles (3 days of glucose deprivation and 10 days of low glucose) to control his fasting blood glucose from 5.9 mmol / L to 4.8 mmol / L, his weight decreased by 3.1 kg, and his blood glucose remained stable during the low glucose period;

[0107] Subject B was selected. Based on the fact that the effect of the glucose withdrawal period was not significant, the system automatically shortened the low glucose period of the second cycle to 7 days, increased the frequency of intervention, and improved the subsequent effect. The safety monitoring process was as follows: when the blood glucose dropped to 3.7 mmol / L, the system successfully triggered a hypoglycemia warning, reminding the user to take timely action to avoid the risk of hypoglycemia.

[0108] according to Figures 7 to 20 As shown, the selected user, Xu (prediabetes), was monitored using the following procedures: initial status: fasting blood glucose 5.9 mmol / L, weight 54.1 kg;

[0109] System execution process:

[0110] If postprandial blood glucose is >6.5 mmol / L, start the first round of glucose-free period (3 days).

[0111] Once the glucose-free period is completed (fasting blood glucose ≤ 5.0 mmol / L) → switch to a low-glucose period (12 days);

[0112] After the fifth glucose-free period: fasting blood glucose stabilized at 4.6 mmol / L, and weight dropped to 50.2 kg.

[0113] according to Figures 21 to 28 As shown, user Yin (type II diabetes) was selected.

[0114] Dynamic adjustment: Due to the high initial blood glucose (fasting 8.3 mmol / L), the system sets a stricter threshold (starting glucose cut-off condition: postprandial > 8.0 mmol / L), extending the low glucose period to 14 days to consolidate the effect.

[0115] In summary, this blood glucose and weight co-management system and method based on dynamic periodic glucose deprivation intervention creates a periodic alternation mechanism of glucose deprivation and low glucose. It utilizes the glucose deprivation period to induce metabolic shifts, while the low glucose period consolidates and enhances metabolic flexibility, overcoming the bottleneck of a single dietary pattern. Simultaneously, it adapts to individual differences by dynamically switching personalized blood glucose thresholds, precisely meeting nutritional needs at different intervention stages through special dietary foods, ensuring safety and adherence. Hardware collaboration enables real-time correlation analysis of blood glucose and weight indicators, and an intelligent decision engine automatically triggers periodic switching. A digital platform facilitates personalized plan development, intelligent recommendation of special dietary foods, real-time data monitoring, and dynamic adjustment, reducing manual intervention and forming a closed-loop management system. Ultimately, it achieves the goals of long-term stable blood glucose control and healthy weight loss.

[0116] The relevant modules involved in this system are all hardware system modules or functional modules that combine computer software programs or protocols with hardware in the prior art. The computer software programs or protocols involved in these functional modules are technologies known to those skilled in the art and are not improvements to this system. The improvement of this system lies in the interaction or connection between the modules, that is, in improving the overall structure of the system to solve the corresponding technical problems that this system aims to address.

[0117] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for coordinated blood glucose and weight management based on dynamic periodic glucose withdrawal intervention, characterized in that, The specific steps include the following: S1. Obtain user's blood glucose and weight data; S2. Based on the comparison results of blood glucose data and personalized thresholds, dynamically trigger high-intensity glucose withdrawal periods or maintenance low-glucose periods; S3. Implement a very low-carbohydrate diet intervention during the sugar-free period and a moderately low-carbohydrate diet intervention during the low-carbohydrate period; S4. Adjust the intervention parameters for the next cycle based on the trend of weight change.

2. A blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention, characterized in that, This includes mobile app modules as user terminals, used for data input, receiving instructions, and viewing reports; The data acquisition and storage module is used to collect basic user data and dynamic monitoring data, and to store historical data and intervention records; Special dietary food database, which categorizes and stores information on special dietary foods with scientific formulas and key parameters labeled; The data analysis module is used to calculate the correlation between blood glucose variability and body weight. The cycle decision engine module switches between sugar-free and low-sugar periods based on set personalized thresholds; The personalized push module outputs corresponding diet and exercise plans based on different stages; The monitoring and early warning module is used for real-time analysis and control effect evaluation, enabling risk warning and dynamic intervention and adjustment; The user interaction module is used to provide special dietary food suggestions and monitoring reminders, output visual reports, and provide user feedback.

3. The blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention according to claim 2, characterized in that, In the data acquisition and storage module, the user's basic data includes age, gender, height, weight, BMI, type of diabetes history, medication history, initial blood glucose level (fasting and postprandial) and control targets (blood glucose target and weight loss target). The dynamic monitoring data includes periodic blood glucose levels (fasting and postprandial specific time points), daily weight, activity level (steps and duration of exercise type), subjective feedback (hunger, energy and sleep), and special dietary food intake records (type, quantity and time).

4. A blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention as described in claim 2, characterized in that, The special dietary food database stores special dietary foods for the sugar-free period and special dietary foods for the low-sugar period separately. The labeled parameters include detailed labeling of each food's net carbohydrate content, fat content, protein content, dietary fiber content, energy value, key nutrients (electrolytes Na / K / Mg, vitamins, specific functional components such as chromium and alpha-lipoic acid), and glycemic index (GI) prediction indicators.

5. A blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention according to claim 2, characterized in that, The cycle decision engine generates personalized plans based on a preset metabolic intervention model and rule base. The personalized threshold is dynamically set according to the user's diabetes type (pre-diabetes and type II), specifically including: 1) Use the collected user basic data and dynamic monitoring data as model input; 2) The model assesses the user's current metabolic status and risk based on the input data and determines the intervention cycle structure, including dynamically generating the initial number of days in the glucose-free period (D1), the number of days in the low-glucose period (D2), and the switching logic based on the blood glucose target value and the rate of weight change. 3) Set the nutritional goals as follows: calculate the daily upper limit of net carbohydrates, protein and fat targets during the glucose-free period, and calculate the daily net carbohydrate target range, protein and fat targets during the low-glucose period; set the criteria for determining blood glucose stability at the end of the glucose-free period as: blood glucose level ≤ target threshold ± 0.5 mmol / L for 48 consecutive hours; 4) Set blood sugar and weight control target ranges, and output a personalized periodic intervention plan in calendar view. Daily nutritional goals include net carbohydrates, protein, fat and energy.

6. A blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention according to claim 2, characterized in that, The personalized recommendation module uses the user's current intervention stage (sugar-free period or low-sugar period), daily nutritional goals, user preferences, and historical feedback as input data for the special dietary food recommendation engine. The data processing procedure is as follows: 1) Based on the current stage, identify the corresponding categories in the special dietary food database (sugar-free period food database and low-sugar period food database); 2) Based on the user's daily nutritional goal of limiting net carbohydrates, select special dietary foods that meet the nutritional parameter requirements from the locked categories; 3) Sort and recommend based on user feedback (including taste preferences and satiety ratings), and calculate recommended intake to meet nutritional goals; 4) Output: A list of recommended special meals (including pictures, names and reasons for recommendation) to be pushed to the user, along with the recommended serving size for each meal on that day; 5) At the same time, provide purchase links for special dietary foods or interfaces for scheduled delivery services.

7. A blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention according to claim 2, characterized in that, The monitoring and early warning module continuously analyzes the input data on blood glucose, weight, activity and special dietary food intake, and tracks blood glucose trends (stability and target achievement rate), weight change trends and periodic goal achievement. Identifying the risk of persistent hypoglycemia, abnormally high blood glucose, and weight plateaus, and setting dynamic intervention and adjustment steps includes: 1) Triggering conditions include early warning signals, deviations from expected results, or switching according to planned cycles; 2) Set the adjustment content as follows: a. Adjustments to the intervention program: Modify the ratio of sugar-free and low-sugar days, switch the timing, and adjust daily nutritional goals, including tightening or relaxing net carbohydrate restrictions; b. Adjustment of special dietary food recommendations: Based on changes in nutritional goals and the adjusted plan for the current stage, update the subsequent special dietary food recommendations in real time.

8. A blood glucose and weight synergistic management system based on dynamic periodic glucose withdrawal intervention according to claim 2, characterized in that, The user interaction module provides guidelines and pairing suggestions for special dietary foods, and sends reminders for monitoring blood glucose, weight, taking special dietary foods and medications, and exercise records. It outputs visual reports, including displaying blood glucose and weight change curves, cycle execution status, and correlation analysis between special dietary food intake and key indicators, to enhance user understanding and compliance. It also provides a user feedback portal to showcase evaluations of the taste and effectiveness of special dietary foods, while connecting with community medical staff to enable remote data monitoring, abnormal intervention, and online consultation.

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