Diet recommendation management method and system based on vital sign state of user

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a diet recommendation management method and system based on the vital sign state of a user, and the method comprises the steps: building a food nutrition information base in advance; generating sign monitoring data of a target user, acquiring vital sign characteristics of the user according to the monitoring data, and calculating the reference intake of personal dietary nutrients at the same time; the user carries out daily healthy diet card punching, diet analysis is carried out, and daily diet recommendation is carried out according to the vital signs of the user and the nutrient elements needing to be ingested every day; acquiring vital sign feedback information of the target user, and updating the daily recommended diet scheme according to the feedback information to obtain an updated daily diet management scheme; and performing health management and vital sign monitoring on the target user according to the updated daily diet management scheme. According to the invention, diet control under the condition of abnormal vital signs of the user can be improved, and life quality is improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a diet recommendation management method and system based on the vital signs status of a user. Background Art

[0002] The diet recommendation management method and system based on the user's vital signs status can provide users with healthy diet recommendations, formulate healthy diet plans, and intervene to help users maintain good physical condition and reduce the risk of disease based on the user's vital signs.

[0003] Traditional dietary methods usually customize dietary recommendations based on the user's disease or personalized nutritional needs. They cannot make timely adjustments based on the user's vital signs, nor can they handle large-scale user dietary recommendation data. At the same time, medical personnel or health management teams can often only provide dietary advice to users after understanding their health status and needs through regular face-to-face visits or telephone consultations. This method limits the timeliness and accuracy of information, and cannot adjust and update management plans in a timely manner. Therefore, how to improve the timeliness of users adjusting recommended diets based on changes in vital signs has become an urgent problem to be solved. Summary of the Invention

[0004] The object of the present invention is to provide a method and system for managing diet recommendations based on the vital signs of a user, so as to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A dietary recommendation management method based on a user's vital signs, comprising:

[0007] Establish a food nutrition information database;

[0008] Calculate the recommended intake of individual dietary nutrients based on the target user's vital sign monitoring data and generate an initial daily diet management plan;

[0009] Quantify health risks based on target users' vital signs monitoring data and determine the weights of each nutrient element;

[0010] Generate a comprehensive food score based on food nutritional information and the weights of each nutrient element, calculate a target diet weighted value based on the target user's physical sign monitoring data, and make target diet recommendations based on the diet adjustment goal, target diet weighted value, and comprehensive food score;

[0011] Obtain food information fed back by users during the management cycle, calculate the user's dietary compliance, and update the dietary recommendation process for the next management cycle based on the user's dietary compliance and the vital sign monitoring data of the target user during the management cycle.

[0012] Furthermore, the user's daily intake data is established, and the recommended intake = standard weight (kg) × energy requirement per unit standard weight, the standard weight (kg) = height (cm) - 105, when 18.5≤BMI<24 and standard weight>recorded weight, the recorded weight is the main factor, and when standard weight<recorded weight, the standard weight is the main factor.

[0013] Furthermore, the target user's blood glucose J1 is compared with a blood glucose threshold JY1. If the target user's blood glucose J1 is greater than the blood glucose threshold JY1, the target user is determined to have high blood glucose, and the first adjustment target is set to 45%-50% carbohydrate ratio. Otherwise, the target user is determined to have normal blood glucose, and the first adjustment target is not set.

[0014] Compare the target user's blood pressure J2 with the blood pressure threshold JY2. If the target user's blood pressure J2 is greater than the blood pressure threshold JY2, the target user is determined to have hypertension, and the second adjustment target is set to sodium intake ≤ 1500 mg / day and potassium intake ≥ 3500 mg / day. Otherwise, the target user is determined to have normal blood pressure and no second adjustment target is set.

[0015] The target user's uric acid J3 is compared with the uric acid threshold JY3. If the target user's uric acid J3 is greater than the uric acid threshold JY3, the target user is determined to have high uric acid, and the third adjustment target is set to purine intake ≤300 mg / day.

[0016] Furthermore, based on the target user's vital sign monitoring data Ji, the risk score Ri of Ji is determined, and Ri = (Ji-JYi) / (JWi-JYi), where JYi is the upper threshold of the i-category data, and JWi is the danger threshold of the i-category monitoring data, i = 1, 2, 3. When i = 1, the monitoring data category is blood sugar, when i = 2, the monitoring data category is blood pressure, and when i = 3, the monitoring data category is uric acid;

[0017] When Ri is greater than or equal to 1, the weight of the i-category monitoring data is set to 3, and the initial weight of the corresponding nutrient element Mi is set to 3. When Ri is greater than 0 and less than 1, the weight of the i-category monitoring data is set to 2, and the initial weight of the corresponding nutrient element Mi is set to 2. When Ri is less than or equal to 0, the weight of the i-category monitoring data is set to 1, and the initial weight of the corresponding nutrient element Mi is set to 1.

[0018] Furthermore, the initial weight Mi of each nutrient element is converted into the weight Si of each nutrient element, and the weight Si is set as

[0019] Furthermore, a food comprehensive score P is generated based on the food nutritional information, and the expression of P is:

[0020] Where Ni is the content of nutrient elements corresponding to the monitoring data of category i in food, and the safety threshold Ni0 and danger threshold Ni1 of the content of nutrient elements corresponding to the monitoring data of category i in food are set at the same time.

[0021] Furthermore, the average value of the i-category monitoring data is calculated based on the target user's historical vital sign monitoring data, recorded as JLi, and JLi is compared with the upper threshold value JYi of the i-category monitoring data. If JLi is less than or equal to JYi, the offset factor of the i-category monitoring data is set to 0. Otherwise, the offset factor of the i-category monitoring data is set to (JLi-JYi) / JYi.

[0022] The target diet weighted value a is constructed based on the offset factor of each category of monitoring data, and the

[0023] The Yi is the weight factor of the i-category data.

[0024] Further, when any Ni in the food is greater than or equal to Ni 1, the food category is determined to be prohibited from intake; when a is greater than a0 and there is Ni0' greater than Ni and less than Ni 1 in the food, the food category is determined to be reduced intake, and Ni0' is the adjusted Ni0; when a is less than or equal to a0 and there is Ni0 greater than Ni and less than Ni 1 in the food, the food category is determined to be reduced intake; when a is greater than a0 and all Ni in the food is less than or equal to Ni0' and the food comprehensive score P is less than or equal to the first safety judgment factor p1, the food category is determined to be normally consumed; when a is greater than a0 and all Ni in the food is less than or equal to Ni0' and the food comprehensive score P is greater than the first safety judgment factor p1 and less than the second safety judgment factor p2, the food category is determined to be reduced intake; when a is greater than a0 and all Ni in the food is less than or equal to Ni0' and the food comprehensive score P is greater than the second safety judgment factor p2, the food category is determined to be When a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is less than or equal to the first safety judgment factor p1, the food category is judged to be normally consumed; when a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is greater than the first safety judgment factor p1 and less than the second safety judgment factor p2, the food category is judged to be reduced intake; when a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is greater than or equal to the second safety judgment factor p2, the food category is judged to be prohibited from intake;

[0025] The comprehensive scores of foods in the food category that are normally consumed are sorted in descending order, and the top E foods are used as recommended foods, and the recommended foods and prohibited foods are pushed to the user.

[0026] Furthermore, the user's daily food information feedback during the management period is matched with the recommended food, and the user's dietary compliance C is calculated based on the matching results. C = c1 / c2, where c1 is the number of days during the management period in which the user's daily food information feedback is successfully matched with the recommended food, and c2 is the number of days in the management period.

[0027] The user's dietary compliance C is compared with the compliance threshold c0. If C is greater than c0, the dietary restrictions are strengthened and the food categories that are to be reduced in intake in the next management cycle are updated to prohibited intake. Otherwise, no update is performed.

[0028] According to another aspect of the present application, a diet recommendation management system based on a user's vital signs is provided, comprising:

[0029] Food database construction module, used to establish a food nutrition information database;

[0030] A diet management module is used to calculate the recommended intake of individual dietary nutrients based on the target user's vital sign monitoring data and generate an initial daily diet management plan;

[0031] A weight determination module is used to quantify health risks based on the target user's vital sign monitoring data and determine the weight of each nutrient element;

[0032] A diet recommendation module generates a comprehensive food score based on food nutritional information and the weights of each nutrient element, calculates a target diet weighted value based on the target user's vital sign monitoring data, and recommends a target diet based on the diet adjustment goal, the target diet weighted value, and the comprehensive food score;

[0033] The dietary feedback module is used to obtain food information feedback from users during the management cycle and calculate the user's dietary compliance. Based on the user's dietary compliance and the vital sign monitoring data of the target user during the management cycle, the dietary recommendation process for the next management cycle is updated.

[0034] The beneficial effects of the present invention are as follows: dietary recommendations are made through automated monitoring of vital signs status, greatly reducing the time and cost of manual intervention and processing; the health status value of the target user is calculated through a preset weighted algorithm, which reflects the user's overall health status, and can quickly and accurately make health judgments on the target user through preset risk thresholds and health status values; this automated health judgment can quickly identify potential risks and problems, and take corresponding measures to intervene in diet in a timely manner, and make daily dietary recommendations for users, thereby improving the efficiency and accuracy of health management; after obtaining feedback information from the target user, the initial plan is updated, and the health management plan can be updated in a timely manner, which can better meet the needs of the user and improve the efficiency of health management. Therefore, the present invention proposes a dietary recommendation management method and system based on the user's vital signs status, which can solve the problem of low health management efficiency of user medical recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 Schematic diagram of the flow of the diet recommendation management method based on the user's vital signs in this embodiment.

[0037] Figure 2 This is a flow chart of the method for generating a diet management plan according to this embodiment.

[0038] Figure 3 Schematic diagram of the flow chart of the method for determining nutrient element weights in this embodiment.

[0039] Figure 4 Schematic diagram of the target diet recommendation method of this embodiment.

[0040] Figure 5 This is a structural diagram of the diet recommendation management system based on the user's vital signs status in this embodiment. DETAILED DESCRIPTION

[0041] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the following detailed description is illustrative rather than restrictive and should not be used to limit the scope of protection of the present invention.

[0042] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0043] See also Figure 1 As shown in FIG, it is a flow chart of the diet recommendation management method based on the user's vital signs status in this embodiment, including:

[0044] Step S101, establishing a food nutrition information database, where food nutrition includes macronutrients and trace elements, wherein the macronutrients include but are not limited to protein, fat and carbohydrates, and the trace elements include but are not limited to vitamins and minerals.

[0045] Specifically, in this embodiment, a food library is set up in advance, and the food library contains food information, which includes food name, classification, nutritional information, etc. The food nutritional information includes: calories, carbohydrates, protein, fat, dietary fiber, cholesterol, purine, GI value, fatty acids (including saturated fatty acids, unsaturated fatty acids, trans fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, n-3 fatty acids), vitamins (including vitamin A (retinol), vitamin B1 (thiamine), vitamin B2 (riboflavin), vitamin C, carotene, vitamin D, vitamin E, folic acid, niacin) and minerals (including sodium, potassium, calcium, phosphorus, magnesium, iron, zinc, selenium, copper, manganese, iodine) content and other nutritional elements.

[0046] Please continue reading Figure 1 As shown, the diet recommendation management method based on the user's vital signs status also includes:

[0047] Step S102, calculate the recommended intake of individual dietary nutrients based on the target user's vital signs monitoring data and generate an initial daily diet management plan, wherein the target user's vital signs monitoring data includes the target user's blood pressure, blood sugar, uric acid, height, BMI and weight.

[0048] See also Figure 2 As shown, the method for generating a dietary management plan includes:

[0049] Step S201 : Calculating the recommended intake of individual dietary nutrients based on the target user's vital sign monitoring data.

[0050] Specifically, establish the user's daily intake data, recommended intake = standard weight (kg) × standard weight requirement coefficient, the standard weight (kg) = height (cm) - 105, when 18.5≤BMI<24 and standard weight>recorded weight, the recorded weight is the main factor, when the standard weight is less than the recorded weight, the standard weight is the main factor, the standard weight requirement coefficient includes the weight requirement coefficient in the first table and the second standard weight requirement coefficient, and the recommended intake is output to the user.

[0051] For example, in this embodiment, the first standard weight requirement coefficient is 1 gram / kilogram, which is the protein requirement coefficient, and the second standard weight requirement coefficient is 30 kcal / kilogram, which is the calorie requirement coefficient; in this embodiment, standard weight requirement coefficients such as dietary fiber and fat can also be added.

[0052] Specifically, the intelligent weight correction algorithm automatically selects a calculation basis based on BMI thresholds (between 18.5 and 24), avoiding errors based on height alone. For example, for obese patients, standard weight is used to prevent overestimation of energy needs.

[0053] Please continue reading Figure 2 As shown, the diet management program generation method further includes:

[0054] Step S202: Evaluate the current health condition of the target user based on the target user's vital sign monitoring data to set a diet adjustment goal.

[0055] Specifically, step S202 compares the target user's blood glucose J1 with a blood glucose threshold JY1. If the target user's blood glucose J1 is greater than the blood glucose threshold JY1, the target user is determined to have high blood glucose, and the first adjustment target is set to a carbohydrate ratio of 45%-50%. Otherwise, the target user is determined to have normal blood glucose, and the first adjustment target is not set.

[0056] Compare the target user's blood pressure J2 with the blood pressure threshold JY2. If the target user's blood pressure J2 is greater than the blood pressure threshold JY2, the target user is determined to have hypertension, and the second adjustment target is set to sodium intake ≤ 1500 mg / day and potassium intake ≥ 3500 mg / day. Otherwise, the target user is determined to have normal blood pressure and no second adjustment target is set.

[0057] The target user's uric acid J3 is compared with the uric acid threshold JY3. If the target user's uric acid J3 is greater than the uric acid threshold JY3, the target user is determined to have high uric acid, and the third adjustment target is set to purine intake ≤300 mg / day.

[0058] For example, in this embodiment, the blood glucose threshold can be set to 6.1 mmol / L, the blood pressure threshold can be set to high pressure 120 mmHg, and the uric acid threshold can be set to 416 μmol / L for men and 357 μmol / L for women. In this embodiment, there is no specific limitation on the setting of the blood glucose threshold, blood pressure threshold and uric acid threshold, and those skilled in the art can freely set them according to their needs. At the same time, those skilled in the art can also add other indicators such as blood lipids to jointly set dietary adjustment goals.

[0059] Specifically, automatic grading is performed through three-dimensional thresholds of blood sugar, blood pressure, and uric acid. Compared with traditional single disease management tools, coordinated intervention of metabolic syndrome is achieved, and at the same time, an association mapping between adjustment targets and other nutritional parameters is established: high blood sugar corresponds to the carbohydrate-water ratio (45-50%), hypertension is associated with sodium-potassium balance (1500mg / 3500mg), and high uric acid binds to purine restriction (300mg / d).

[0060] Please continue reading Figure 1As shown, the diet recommendation management method based on the user's vital signs status also includes:

[0061] Step S103: quantify the health risk based on the target user's physical sign monitoring data and determine the weight of each nutrient element.

[0062] Please continue reading Figure 3 As shown, the method for determining the nutrient element weights includes:

[0063] Step S301: quantify health risks based on target user's vital sign monitoring data and determine initial weights of nutritional elements.

[0064] Specifically, step S201 determines the risk score Ri of Ji based on the target user's vital sign monitoring data Ji, and sets Ri = (Ji-JYi) / (JWi-JYi), where JYi is the upper threshold of the i-category data, and JWi is the danger threshold of the i-category monitoring data, i = 1, 2, 3. When i = 1, the monitoring data category is fasting blood glucose, when i = 2, the monitoring data category is blood pressure, and when i = 3, the monitoring data category is uric acid;

[0065] When Ri is greater than or equal to 1, the weight of the i-category monitoring data is set to 3, and the initial weight of the corresponding nutrient element Mi is set to 3. When Ri is greater than 0 and less than 1, the weight of the i-category monitoring data is set to 2, and the initial weight of the corresponding nutrient element Mi is set to 2. When Ri is less than or equal to 0, the weight of the i-category monitoring data is set to 1, and the initial weight of the corresponding nutrient element Mi is set to 1.

[0066] For example, in this embodiment, JW1 can be set to 7.0 mmol / L, JW2 can be set to 180 mmHg, and JW3 can be set to 480 μmol / L. In this embodiment, no specific limitation is imposed on the above values, and those skilled in the art can freely set them according to their needs.

[0067] Specifically, a relative proportion calculation model maps a user's actual physiological indicators to medical thresholds, achieving a smooth risk transition from "normal" to "high-risk." This allows for more accurate identification of subtle differences in a user's current health status, providing a precise basis for personalized nutritional regulation.

[0068] Please continue reading Figure 3 As shown, the method for determining nutrient element weights further includes:

[0069] Step S302 : normalize the initial weights of the various nutrient elements to determine the weights of the various nutrient elements.

[0070] Specifically, the initial weight Mi of each nutrient element is converted into the weight Si of each nutrient element, and the weight Si is set as

[0071] Specifically, through mathematical transformation, the weights of multi-dimensional health parameters are constrained to the same standard range, eliminating the comparability barriers between parameters of different dimensions, so that heterogeneous nutrients such as carbohydrates, purines, and sodium can participate fairly in the comprehensive evaluation.

[0072] Please continue reading Figure 1 As shown, the diet recommendation management method based on the user's vital signs status also includes:

[0073] Step S104, generating a comprehensive food score based on food nutritional information and the weights of each nutritional element, calculating a target diet weighted value based on the target user's physical sign monitoring data, and making a target diet recommendation based on the diet adjustment target, the target diet weighted value and the comprehensive food score.

[0074] See also Figure 4 As shown, the target diet recommendation method includes:

[0075] Step S401: Generate a comprehensive food score based on food nutritional information and the weights of each nutritional element.

[0076] Specifically, based on the food nutritional information, a food comprehensive score P is generated, and the expression of P is:

[0077] Wherein, Ni is the content of the nutrient element corresponding to the i-category monitoring data in the food, and the safety threshold value Ni0 and the danger threshold value Ni1 of the content of the nutrient element corresponding to the i-category monitoring data in the food are set at the same time; the nutrient element content is the content of a specific nutrient in the food (the content per 100 grams of edible part), and the unit is determined according to the nutrient type, such as purine content (mg / 100g), sodium content (mg / 100g), etc.; the safety threshold is the upper limit of the nutrient element content that the user can normally ingest, and no restriction is required below this value, for example, the purine safety threshold is ≤50mg / 100g; the danger threshold is the lower limit of the nutrient element content that the user must strictly prohibit from ingesting, and it is completely inedible above this value, for example, the purine danger threshold is ≥150mg / 100g; the nutrient element weight reflects the priority weight of the nutrient element to the user's health, and needs to be dynamically adjusted according to the user's current health problems and normalized to 0-1. The higher the value, the more strictly the nutrient needs to be controlled.

[0078] Specifically, a nonlinear calculation model is used to generate exponential feedback on excessive nutrients. Even food ingredients that slightly exceed safety thresholds (such as critically high-purine ingredients) will have their risk significantly amplified and flagged, strictly guarding against potential health threats.

[0079] It is worth noting that, in this embodiment, when calculating the comprehensive score of food, only the value of Ni is used without considering its physical meaning.

[0080] See also Figure 4 As shown, the target diet recommendation method includes:

[0081] Step S402: Calculate the target diet weighted value based on the target user's historical vital sign monitoring data.

[0082] Specifically, the average value of the i-category monitoring data is calculated based on the target user's historical vital sign monitoring data, recorded as JLi, and JLi is compared with the upper threshold value JYi of the i-category monitoring data. If JLi is less than or equal to JYi, the offset factor of the i-category monitoring data is set to 0. Otherwise, the offset factor of the i-category monitoring data is set to (JLi-JYi) / JYi.

[0083] The target diet weighted value a is constructed based on the offset factor of each category of monitoring data, and is set as:

[0084] The Yi is the weight factor of category i data.

[0085] Specifically, the system dynamically adjusts nutrient restriction thresholds based on trend analysis of users' long-term health data. For users with persistently abnormal indicators, the system gradually tightens the permitted ranges for relevant nutrients, forming an adaptive strategy that evolves with their health status.

[0086] For example, in this embodiment, the optimal value of Y1 is 0.4, the optimal value of Y2 is 0.5, and the optimal value of Y3 is 0.1; this embodiment does not specifically limit the setting of each weight factor, and those skilled in the art can freely set it according to needs.

[0087] Step S403: classify the food based on the target diet weighted value and the food comprehensive score, and make target diet recommendations based on the classification results.

[0088] Specifically, in step S302, when any Ni in the food is greater than or equal to Ni 1, the food category is determined to be prohibited from intake; when a is greater than a0 and there is Ni0' greater than Ni and less than Ni 1 in the food, the food category is determined to be reduced intake, and Ni0' is the adjusted Ni 0; when a is less than or equal to a0 and there is Ni0 greater than Ni and less than Ni 1 in the food, the food category is determined to be reduced intake; when a is greater than a0 and all Ni in the food are less than or equal to Ni0' and the food comprehensive score P is less than or equal to the first safety judgment factor p1, the food category is determined to be normally consumed; when a is greater than a0 and all Ni in the food are less than or equal to Ni0' and the food comprehensive score P is greater than the first safety judgment factor p1 and less than the second safety judgment factor p2, the food category is determined to be reduced intake; when a is greater than a0 and all Ni in the food are less than or equal to Ni0' and the food comprehensive score P is greater than the second safety judgment factor p2, the food category is determined to be prohibited from intake; When a is equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is less than or equal to the first safety judgment factor p1, the food category is judged to be normally consumed; when a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is greater than the first safety judgment factor p1 and less than the second safety judgment factor p2, the food category is judged to be reduced in intake; when a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is greater than or equal to the second safety judgment factor p2, the food category is judged to be prohibited from intake; the Ni0'=Ni0×(1-0.25a);

[0089] The step S302 sorts the comprehensive scores of foods in the food category of normal intake in descending order, takes the top E foods as recommended foods, and pushes the recommended foods and prohibited foods to the user.

[0090] For example, in this embodiment, p1 can be set to 20, p2 can be set to 50, and E can be set to 10. In this embodiment, there is no specific limitation on the setting of each data, and those skilled in the art can freely set it according to needs.

[0091] Please continue reading Figure 1 As shown, the diet recommendation management method based on the user's vital signs status also includes:

[0092] Step S105: obtaining the food information fed back by the user during the management period, calculating the user's dietary compliance, and updating the dietary recommendation process for the next management period based on the user's dietary compliance.

[0093] Specifically, the user's daily food information feedback during the management period is matched with the recommended food, and the user's dietary compliance C is calculated based on the matching results. Set C = c1 / c2, where c1 is the number of days during the management period in which the user's daily food information feedback is successfully matched with the recommended food, and c2 is the number of days in the management period.

[0094] The user's dietary compliance C is compared with the compliance threshold c0. If C is greater than c0, the dietary restrictions are strengthened and the food categories that are to be reduced in intake in the next management cycle are updated to prohibited intake. Otherwise, no update is performed.

[0095] For example, in this embodiment, the compliance threshold can be set to 0.8 and the management period can be set to 30 days; in this embodiment, there is no specific limitation on the setting of the compliance threshold and the management period, and those skilled in the art can freely set them according to their needs.

[0096] Specifically, based on the compliance determination results, the control strictness is intelligently adjusted, and restrictions are gradually strengthened for users with strong execution capabilities (such as upgrading foods that need to be reduced to prohibited foods) to accelerate the achievement of health goals; for users with low compliance, the current strategy is maintained to avoid excessive restrictions that may cause resistance, and to achieve flexible adjustment of the management rhythm.

[0097] See also Figure 5 As shown, the present invention also provides a diet recommendation management system based on the user's vital signs, comprising:

[0098] Food database construction module, used to establish a food nutrition information database;

[0099] A diet management module is used to calculate the recommended intake of individual dietary nutrients based on the target user's vital sign monitoring data and generate an initial daily diet management plan;

[0100] A weight determination module is used to quantify health risks based on the target user's vital sign monitoring data and determine the weight of each nutrient element;

[0101] A diet recommendation module generates a comprehensive food score based on food nutritional information and the weights of each nutrient element, calculates a target diet weighted value based on the target user's vital sign monitoring data, and recommends a target diet based on the diet adjustment goal, the target diet weighted value, and the comprehensive food score;

[0102] The dietary feedback module is used to obtain food information feedback from users during the management cycle and calculate the user's dietary compliance. Based on the user's dietary compliance and the vital sign monitoring data of the target user during the management cycle, the dietary recommendation process for the next management cycle is updated.

[0103] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in this field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.

Claims

1. A diet recommendation management method based on the user's vital signs, characterized in that: include: Establish a food nutrition information database; Calculate the recommended intake of individual dietary nutrients based on the target user's vital sign monitoring data and generate an initial daily diet management plan; Quantify health risks based on target users' vital signs monitoring data and determine the weight of each nutrient element; Generate a comprehensive food score based on food nutritional information and the weights of each nutrient element, calculate a target diet weighted value based on the target user's physical sign monitoring data, and make target diet recommendations based on the diet adjustment goal, target diet weighted value, and comprehensive food score; Obtain food information fed back by users during the management cycle, calculate the user's dietary compliance, and update the dietary recommendation process for the next management cycle based on the user's dietary compliance and the vital sign monitoring data of the target user during the management cycle.

2. The dietary recommendation management method based on the user's vital signs according to claim 1, characterized in that: Establish user's daily intake data, recommended intake = standard weight (kg) × energy requirement per unit standard weight, the standard weight (kg) = height (cm) - 105, when 18.5≤BMI<24 and standard weight>recorded weight, the recorded weight is the main factor, when standard weight<recorded weight, the standard weight is the main factor.

3. The dietary recommendation management method based on the user's vital signs according to claim 2, characterized in that: Compare the target user's blood sugar J1 with the blood sugar threshold JY1. If the target user's blood sugar J1 is greater than the blood sugar threshold JY1, the target user is determined to have high blood sugar, and the first adjustment target is set to 45%-50% carbohydrate ratio. Otherwise, the target user is determined to have normal blood sugar, and no first adjustment target is set. Compare the target user's blood pressure J2 with the blood pressure threshold JY2. If the target user's blood pressure J2 is greater than the blood pressure threshold JY2, the target user is determined to have hypertension, and the second adjustment target is set to sodium intake ≤ 1500 mg / day and potassium intake ≥ 3500 mg / day. Otherwise, the target user is determined to have normal blood pressure and no second adjustment target is set. The target user's uric acid J3 is compared with the uric acid threshold JY3. If the target user's uric acid J3 is greater than the uric acid threshold JY3, the target user is determined to have high uric acid, and the third adjustment target is set to purine intake ≤300 mg / day.

4. The dietary recommendation management method based on the user's vital signs according to claim 3, characterized in that: Determine Ji's risk score Ri based on the target user's vital sign monitoring data Ji, and set Ri = (Ji-JYi) / (JWi-JYi), where JYi is the upper threshold of category i data, and JWi is the danger threshold of category i monitoring data, i = 1, 2, 3. When i = 1, the monitoring data category is blood sugar, when i = 2, the monitoring data category is blood pressure, and when i = 3, the monitoring data category is uric acid; When Ri is greater than or equal to 1, the weight of the i-category monitoring data is set to 3, and the initial weight of the corresponding nutrient element Mi is set to 3. When Ri is greater than 0 and less than 1, the weight of the i-category monitoring data is set to 2, and the initial weight of the corresponding nutrient element Mi is set to 2. When Ri is less than or equal to 0, the weight of the i-category monitoring data is set to 1, and the initial weight of the corresponding nutrient element Mi is set to 1.

5. The dietary recommendation management method based on the user's vital signs according to claim 4, characterized in that: Convert the initial weight Mi of each nutrient element into the weight Si of each nutrient element, and set 6. The dietary recommendation management method based on the user's vital signs according to claim 5, characterized in that: Generate a comprehensive food score P based on the food nutritional information. The expression of P is: Where Ni is the content of nutrient elements corresponding to the monitoring data of category i in food, and the safety threshold Ni0 and danger threshold Ni1 of the content of nutrient elements corresponding to the monitoring data of category i in food are set at the same time.

7. The dietary recommendation management method based on the user's vital signs according to claim 6, characterized in that: Based on the target user's historical vital sign monitoring data, calculate the average value of the i-category monitoring data, recorded as JLi, and compare JLi with the upper threshold value JYi of the i-category monitoring data. If JLi is less than or equal to JYi, the offset factor of the i-category monitoring data is set to 0. Otherwise, the offset factor of the i-category monitoring data is set to (JLi-JYi) / JYi; The target diet weighted value a is constructed based on the offset factor of each category of monitoring data, and the The Yi is the weight factor of category i data.

8. The dietary recommendation management method based on the user's vital signs according to claim 7, characterized in that: When any Ni in the food is greater than or equal to Ni 1, the food category is determined to be prohibited from intake; when a is greater than a0 and there is Ni0' greater than Ni and less than Ni 1 in the food, the food category is determined to be reduced intake, and Ni 0' is the adjusted Ni0; when a is less than or equal to a0 and there is Ni0 greater than Ni and less than Ni 1 in the food, the food category is determined to be reduced intake; when a is greater than a0 and all Ni in the food are less than or equal to Ni0' and the food comprehensive score P is less than or equal to the first safety judgment factor p1, the food category is determined to be normally consumed; when a is greater than a0 and all Ni in the food are less than or equal to Ni0' and the food comprehensive score P is greater than the first safety judgment factor p1 and less than the second safety judgment factor p2, the food category is determined to be reduced intake; when a is greater than a0 and all Ni in the food are less than or equal to Ni0' and the food comprehensive score P is greater than the second safety judgment factor p2, the food category is determined to be prohibited from intake; When a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is less than or equal to the first safety judgment factor p1, the food category is judged to be normally consumed; When a is less than or equal to a0, all Ni in the food is less than or equal to Ni0, and the food comprehensive score P is greater than the first safety judgment factor p1 and less than the second safety judgment factor p2, the food category is determined to be reduced intake; When a is less than or equal to a0, all Ni in the food is less than or equal to Ni 0, and the food comprehensive score P is greater than or equal to the second safety judgment factor p2, the food category is determined to be prohibited from intake; The comprehensive scores of foods in the food category that are normally consumed are sorted in descending order, and the top E foods are used as recommended foods, and the recommended foods and prohibited foods are pushed to the user.

9. The dietary recommendation management method based on the user's vital signs according to claim 8, characterized in that: Match the user's daily food information with the recommended food during the management period, and calculate the user's dietary compliance C based on the matching results. Set C = c1 / c2, where c1 is the number of days in the management period where the user's daily food information is successfully matched with the recommended food, and c2 is the number of days in the management period; The user's dietary compliance C is compared with the compliance threshold c0. If C is greater than c0, the dietary restrictions are strengthened and the food categories that are to be reduced in intake in the next management cycle are updated to prohibited intake. Otherwise, no update is performed.

10. A diet recommendation management system based on user vital signs, applied to the diet recommendation management method based on user vital signs according to any one of claims 1 to 9, characterized in that: include: Food database construction module, used to establish a food nutrition information database; A diet management module is used to calculate the recommended intake of individual dietary nutrients based on the target user's vital sign monitoring data and generate an initial daily diet management plan; A weight determination module is used to quantify health risks based on the target user's vital sign monitoring data and determine the weight of each nutrient element; A diet recommendation module generates a comprehensive food score based on food nutritional information and the weights of each nutrient element, calculates a target diet weighted value based on the target user's vital sign monitoring data, and recommends a target diet based on the diet adjustment goal, the target diet weighted value, and the comprehensive food score; The dietary feedback module is used to obtain food information feedback from users during the management period and calculate the user's dietary compliance. Based on the user's dietary compliance and the vital sign monitoring data of the target user during the management period, the dietary recommendation process for the next management period is updated.

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