A method for optimizing dietary energy intake in obese people

Abstract

The present invention relates to the technical field of intelligent nutrition management, and in particular to a method for optimizing dietary energy intake for obese people, the method comprising: determining nutritional characteristic values ​​of various foods according to a nutrient content sequence and performing a sorting operation to obtain a main nutrient data string of the various foods; analyzing each main nutrient data string and performing a corresponding first-class energy labeling; determining the energy density level and expansion level of various foods and performing a corresponding second-class energy labeling; based on the first-class energy labeling result and the second-class energy labeling result, correcting a primary energy sequence and adding a label stamp to obtain an actual energy sequence table; periodically obtaining parameters of a person to be optimized, inputting the parameters of the person to be optimized into a linear regression model to output an actual progress direction; and combining the actual energy sequence table, the first-class energy labeling result and the second-class energy labeling result according to the actual progress direction to output a dietary energy prediction result.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent nutrition management, and in particular to a method for optimizing dietary energy intake for obese people. Background Art

[0002] Obesity is mainly caused by energy intake exceeding energy expenditure, resulting in excessive accumulation of fat in the body; long-term obesity not only affects appearance, but more importantly, it significantly increases the risk of chronic diseases such as diabetes, cardiovascular disease, hypertension, and hyperlipidemia; therefore, optimizing the dietary energy intake of obese people is of great significance for the prevention and control of obesity and its related complications; but currently, dietary energy calculation is easily affected by eating habits, and researchers need to have a high level of knowledge of food nutrient composition and its energy content, and the calculation process is complicated, which consumes a lot of manpower and material resources.

[0003] Chinese patent application publication number CN112116987A discloses a dietary matching method and system through multi-attribute decision making, the purpose of which is to provide users with a set of dietary plans that meet dietary standards by considering individual differences of users. The following steps are included: calculating the nutrient content of each plan; according to personal information, the system formulates dietary standards and fine-tunes the dietary standards; calculating the cosine similarity between the dietary plan and the dietary standards to generate candidate dietary plans; users can independently replace dishes in the candidate dietary plans; screening dietary plans according to energy ratio, and the user selects one of the plans; recombining the dishes in the plan to form multiple dietary plans, and constructing a decision matrix; using the interval TOPSIS (top-up to ideal solution ranking method) method to obtain the optimal dietary plan.

[0004] It can be seen from this that current catering recommendations are only for short-term periods and are unable to make long-term predictions, which leads to the inability to accurately calculate long-term planning of dietary energy. Summary of the invention

[0005] To this end, the purpose of the present invention is to provide a method for optimizing dietary energy intake for obese people, which is used to overcome the problem that current catering recommendations are only for a short period of time and cannot be predicted for a long period of time, resulting in the inability to accurately calculate long-term planning of dietary energy.

[0006] To achieve the above object, the present invention provides a method for optimizing dietary energy intake for obese people, comprising:

[0007] Based on the food information database, preliminary classification is performed according to food attributes to obtain food data sets with different attributes;

[0008] For any attribute food data set, obtain the nutrient content sequence of various foods in the attribute food data set, identify the nutrient content sequence, and determine the nutrient characteristic values ​​of various foods;

[0009] Sorting each food in the attribute food data set according to each determined nutritional characteristic value to obtain an energy sequence;

[0010] Select nutrients from the nutrient content sequence according to the second screening standard to obtain main nutrient content data strings of various foods;

[0011] Analyze the data strings of each main nutrient component, and assign a corresponding energy label to each food according to the analysis results;

[0012] Determining the energy density level and the expansion level of various foods according to the nutrient content sequence, and performing corresponding second-class energy labeling on various foods according to the energy density level and the expansion level;

[0013] Based on the first-class energy marking result and the second-class energy marking result, the primary energy sequence is corrected and a marking stamp is added to obtain an actual energy sequence table;

[0014] According to a preset acquisition cycle, periodically acquire the parameters of the personnel to be optimized, and input the parameters of the personnel to be optimized into a linear regression model to output the actual progress direction;

[0015] Combining the actual energy sequence table, the first type of energy labeling result and the second type of energy labeling result according to the actual progress direction to output a dietary energy prediction result;

[0016] Among them, the second screening standard is to select several nutrients whose actual content is greater than or equal to the preset second standard content.

[0017] Furthermore, the process of identifying the nutrient content sequence to determine the nutrient characteristic values ​​of various foods includes:

[0018] For any kind of food, the total number of nutrient types of the food is obtained, and the nutrient coverage is determined according to the total number of nutrient types;

[0019] Obtaining the number of first nutrient types of the food according to the first screening standard, and determining the nutrient density according to the number of the first nutrient types;

[0020] Among them, the nutritional characteristic values ​​include: the nutritional coverage and the nutrient density; the first screening criterion is to select a number of nutrients whose actual content is greater than or equal to a preset first standard content.

[0021] Furthermore, the process of sorting the foods in the attribute food data set according to the determined nutritional characteristic values ​​to obtain an energy sequence includes:

[0022] Determining the number of items in the nutrient coverage and the nutrient density that meet a single determination condition;

[0023] Determining the energy level of various foods according to the number of items, and grading and classifying various foods according to the energy level to obtain a plurality of food data groups;

[0024] Based on the classification results, the initial energy scores of various foods are calculated according to the nutrient coverage and the nutrient density, and various foods in each food data group are sorted according to the initial energy scores;

[0025] The primary sorting results in each food data group are integrated to obtain the primary energy sequence.

[0026] Furthermore, the process of determining the number of items in the nutrient coverage and the nutrient density that meet a single determination condition includes:

[0027] Determining whether the nutrient coverage meets the single determination condition according to the total number of nutrient types and a preset first evaluation value;

[0028] Determining whether the nutrient density meets the single determination condition according to the number of the first nutrient types and a preset second evaluation value;

[0029] Wherein, based on the total number of nutrient types being greater than or equal to the first evaluation value, it is determined that the nutrient coverage meets the single determination condition; based on the total number of nutrient types being less than the first evaluation value, it is determined that the nutrient coverage does not meet the single determination condition;

[0030] Based on the fact that the number of the first nutrient types is greater than or equal to the second evaluation value, it is determined that the nutrient density meets the single determination condition; based on the fact that the number of the first nutrient types is less than the second evaluation value, it is determined that the nutrient density does not meet the single determination condition.

[0031] Furthermore, the process of determining the energy levels of various foods according to the number of items, and grading and classifying various foods according to the energy levels to obtain a plurality of food data groups includes:

[0032] For any kind of food, when the number of items is 2, the energy level is determined to be level one; when the number of items is 1, the energy level is determined to be level two; when the number of items is 0, the energy level is determined to be level three;

[0033] Various foods are graded and divided according to the graded and divided results to obtain a primary food data group, a secondary food data group and a tertiary food data group.

[0034] Furthermore, the process of labeling various foods with a corresponding type of energy according to the analysis results includes:

[0035] For any main nutrient component data string, obtain the number of main nutrient types in the main nutrient component data string;

[0036] The food corresponding to the main nutrient component data string is marked with a type of energy according to the number of types of the main nutrients.

[0037] Furthermore, the process of marking the food corresponding to the main nutrient component data string with a type of energy according to the number of main nutrient types includes:

[0038] If the number of main nutrients is equal to 0, the food is not marked;

[0039] Based on the number of main nutrient types being equal to 1, the food is labeled as: single type;

[0040] Based on the number of the main nutrients being greater than 1, obtaining the main content of each main nutrient;

[0041] According to each main content combined with the second standard content, a type of energy labeling is determined as a composite type, or a biased type.

[0042] Furthermore, the process of determining a type of energy labeling as a composite type or a biased type according to each main content combined with the second standard content includes:

[0043] Calculate the content difference between each main content and the second standard content;

[0044] Determining a difference ratio according to the content difference and a preset third evaluation value;

[0045] Based on the difference ratio not being 0, it is determined that the energy label type of the food is the composite type;

[0046] Based on the difference ratio being 0, it is determined that the energy label type of the food is the biased type.

[0047] Furthermore, the process of labeling various foods with the corresponding second-class energy according to the energy density level and the expansion degree level includes:

[0048] For any food, obtain the actual energy content and target nutrients of the food;

[0049] Determining the energy density level as low energy density, medium energy density or high energy density according to the actual energy content;

[0050] Determining the overswelling level as low overswelling, medium overswelling or high overswelling according to the target nutrient;

[0051] Based on the energy density level and the expansion degree level, the second energy labeling type of various foods is determined as A-type food, B-type food, and C-type food.

[0052] Furthermore, the process of correcting the primary energy sequence and adding a mark stamp based on the first energy marking result and the second energy marking result to obtain an actual energy sequence table includes:

[0053] The attribute food data set is screened based on the first energy labeling result and the second energy labeling result to obtain a labeled food data cluster;

[0054] Identifying the labeled food data clusters to determine the actual labeled categories and actual labeled types of various foods;

[0055] Correcting the initial energy scores of various foods according to the actual marking categories and the actual marking types to obtain actual energy scores;

[0056] The primary energy sequence is reordered based on the actual energy score to obtain an actual energy sequence, and the mark stamp is added to the actual energy sequence based on the first type of energy marking result and the second type of energy marking result to obtain the actual energy sequence table.

[0057] Compared with the prior art, the beneficial effects of the present invention are that, through the determination of the food information database and the nutritional characteristic values, the food is scientifically classified and evaluated to ensure the nutritional balance of the recipe; the food is sorted and corrected to generate a personalized energy sequence, which is helpful to achieve the control of energy intake; through the preset screening criteria, the main nutrients are selected to avoid nutrient deficiency or excess and promote nutritional balance; in combination with the energy density and expansion level, the food is more accurately labeled with the second type of energy, which is helpful to improve the actual application effect of the recipe; the parameters of the personnel to be optimized are periodically obtained, and the actual progress direction is output in combination with the linear regression model to achieve dynamic adjustment and optimization of the dietary energy prediction results; according to the actual progress direction and the energy sequence, accurate dietary energy prediction results are output to provide strong support for nutritional management and healthy diet; through the steps of scientific classification, determination of nutritional characteristic values, correction of energy sequence, etc., the efficiency of nutritional intake is improved and the waste of nutrients is avoided; through scientific classification, evaluation, sorting and correction, as well as dynamic adjustment and optimization, the accuracy of dietary energy prediction results is achieved, and a personalized nutritional intervention plan is provided, which is helpful to achieve the optimization of dietary energy intake of obese people.

[0058] By calculating the nutritional coverage, we can understand the number of types of chemical substances contained in food that can provide energy or support body functions, which helps to judge the nutritional diversity of food; by calculating the nutrient density, we can understand the relationship between the content of specific nutrients in food and the total number of nutrient types, which helps to judge the richness of certain key nutrients in food; by setting the first standard content and the second standard content, we can standardize the screening of foods to ensure the fairness and consistency of the evaluation; considering the influence of food properties and nutrient types, we can more accurately evaluate the nutritional characteristic values ​​of different foods; by analyzing these nutritional characteristic values ​​of food, we can better plan a healthy diet and ensure adequate intake of nutrients while avoiding over or undernutrition.

[0059] By judging the number of items that meet a single judgment criterion in nutrient coverage and nutrient density, the energy level of food can be evaluated, which helps to identify foods of different energy levels; by grading and dividing various foods according to their energy levels, food data groups of different energy levels can be obtained, which helps to classify and analyze foods in more detail; based on nutrient coverage and nutrient density, the initial energy scores of various foods are calculated, and the foods are sorted according to the scores, which helps to more accurately evaluate the energy value of foods; the sorting results within each food data group are integrated to obtain an energy sequence, which helps to comprehensively evaluate and compare foods; based on the energy level and energy score of food, a healthy diet can be planned to ensure the intake of an appropriate amount of energy while avoiding excessive or insufficient energy intake; by quantifying the intrinsic energy characteristics of food, it helps to evaluate the energy value of food more scientifically and accurately.

[0060] By judging the number of main nutrients in food, the refined classification of food is achieved; it not only helps to understand the nutritional composition of food more clearly, but also guides healthier dietary choices; for example, a single type of food may be more suitable for people with specific dietary needs, while compound or biased types of food can provide more comprehensive nutrition; by calculating the difference between the content of each main nutrient and the second standard content, and combining the preset third evaluation value to determine the macro or trace classification of nutrients, this method is scientific and objective; it avoids errors caused by subjective judgment, making energy labeling more accurate and reliable; by energy labeling of food, healthy diets can be better planned to ensure the intake of appropriate amounts of nutrients while avoiding over or undernutrition; the main nutrients of each food are quantified and their nutrient types and contents are marked, making the nutritional content of food more transparent.

[0061] By calculating energy density, we can understand the energy contained in food per unit weight, which helps to judge the energy content of food; by calculating expansion intensity, we can understand the degree of expansion of food during digestion, which helps to judge the nutritional characteristics and energy type of food; according to the energy density level and expansion level, food can be labeled as Class A, Class B or Class C, which helps to distinguish different types of food, thereby guiding the selection and matching of food; by analyzing the energy density level and expansion level of food, we can better plan a healthy diet and ensure the intake of an appropriate amount of energy while avoiding excessive or insufficient energy intake; by comprehensively considering the actual energy content and target nutrients of food, we can comprehensively evaluate the energy density and expansion level of food; comprehensive evaluation helps to understand the nutritional value of food more accurately; according to the energy density and expansion level, foods are divided into Class A, Class B and Class C, and this classification method is both scientific and practical; it can meet the expansion degree without causing excessive energy intake, and help choose a healthier diet, thereby preventing obesity and related diseases.

[0062] By combining Class I energy markers and Class II energy markers, the actual energy value of food can be evaluated more comprehensively; the comprehensive evaluation method improves the accuracy and scientificity of energy evaluation; for foods with both Class I energy markers and Class II energy markers, the correction mode can be turned on to correct the initial energy score according to the specific attributes of the food; this makes the energy score closer to the actual nutritional value of the food, which helps to make more reasonable dietary choices; based on the corrected actual energy score, the primary energy sequence is re-sorted to obtain the actual energy sequence, making the energy sequence more reasonable and able to more accurately reflect the energy differences between foods; on the basis of the actual energy sequence, mark stamps are added according to the Class I and Class II energy marking results to form an actual energy sequence table; the marking method enhances the transparency of information, making it possible to more intuitively understand the nutritional characteristics and energy value of food.

[0063] By setting the acquisition cycle to one week, the timeliness and dynamism of the data are ensured; high-frequency data collection enables health management to respond more quickly to changes in the physical condition of the person to be optimized, so as to adjust the dietary plan and other health intervention measures in a timely manner; through a strict data collation and verification process, the accuracy and completeness of the parameter information input into the linear regression model are ensured; the accuracy of the model prediction is improved, making the output actual progress direction and dietary energy prediction results more reliable; the linear regression model is used to predict the direction of health progress, combining the personalized physiological parameters and health indicators of the person to be optimized; the prediction method can more accurately reflect the health status and change trend of the person to be optimized, and provide strong support for subsequent dietary planning; the actual progress direction is combined with the actual energy sequence table, and the nutritional value and health benefits of food are comprehensively considered; the comprehensive evaluation method makes the dietary energy prediction results more comprehensive and scientific, and provides personalized dietary plans or advisory guidance for the person to be optimized; through regular monitoring, prediction and adjustment of dietary plans, the continuous health management process helps to promote the improvement of the overall health status of the person to be optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of a process for optimizing dietary energy intake for obese people according to an embodiment of the present invention;

[0065] Figure 2 A flow chart of generating a primary energy sequence in a method for optimizing dietary energy intake for obese people according to an embodiment of the present invention;

[0066] Figure 3 It is a logic diagram for determining energy levels in a method for optimizing dietary energy intake for obese people according to an embodiment of the present invention;

[0067] Figure 4 This is a flow chart of two types of energy labeling in the method for optimizing dietary energy intake for obese people according to an embodiment of the present invention. DETAILED DESCRIPTION

[0068] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0069] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0070] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0071] See also Figure 1 As shown, this embodiment provides a method for optimizing dietary energy intake for obese people, comprising:

[0072] Step S100, based on the food information database, preliminary classification is performed according to food attributes to obtain a food data set of each attribute;

[0073] Step S200, for any attribute food data set, obtaining the nutrient content sequence of various foods in the attribute food data set, identifying the nutrient content sequence, so as to determine the nutrient characteristic values ​​of various foods;

[0074] Step S300, sorting each food in the attribute food data set according to the determined nutritional characteristic values ​​to obtain an energy sequence;

[0075] Step S400, selecting nutrients from the nutrient content sequence according to a second screening standard to obtain a main nutrient data string of various foods;

[0076] Step S500, analyzing each main nutrient component data string, and marking each food with a corresponding energy type according to the analysis result;

[0077] Step S600, determining the energy density level and the expansion level of various foods according to the nutrient content sequence, and performing corresponding second-category energy labeling on various foods according to the energy density level and the expansion level;

[0078] Step S700, based on the first energy marking result and the second energy marking result, the primary energy sequence is corrected and a mark is added to obtain an actual energy sequence table;

[0079] Step S800, periodically acquiring parameters of personnel to be optimized according to a preset acquisition cycle, and inputting the parameters of personnel to be optimized into a linear regression model to output an actual progress direction;

[0080] Step S900, combining the actual energy sequence table, the first type of energy labeling result and the second type of energy labeling result according to the actual progress direction to output a dietary energy prediction result;

[0081] Among them, the second screening standard is to select several nutrients whose actual content is greater than or equal to the preset second standard content.

[0082] In this embodiment, the food attributes include: meat, fruit, eggs, cereals, vegetables, etc.; in this embodiment, when BMI≥28, it is determined to be obese.

[0083] Specifically, the embodiment of the present invention classifies and evaluates food scientifically through the determination of food information database and nutritional characteristic values ​​to ensure the nutritional balance of the recipe; sorts and corrects food to generate a personalized energy sequence, which helps to control energy intake; selects main nutrients through preset screening standards to avoid nutrient deficiency or excess and promote nutritional balance; combines energy density and expansion level to more accurately label food with two types of energy, which helps to improve the actual application effect of the recipe; periodically obtains the parameters of the personnel to be optimized, combines with the linear regression model, outputs the actual progress direction, and realizes dynamic adjustment and optimization of the dietary energy prediction results; outputs accurate dietary energy prediction results based on the actual progress direction and energy sequence, and provides strong support for nutritional management and healthy diet; improves the efficiency of nutritional intake and avoids nutrient waste through scientific classification, nutritional characteristic value determination, energy sequence correction and other steps; achieves the accuracy of dietary energy prediction results through scientific classification, evaluation, sorting and correction, as well as dynamic adjustment and optimization, provides a personalized nutritional intervention plan, and helps to optimize the dietary energy intake of obese people.

[0084] Specifically, in this embodiment, the process of identifying the nutrient content sequence to determine the nutrient characteristic values ​​of various foods includes:

[0085] Step S210, for any kind of food, obtaining the total number of nutrient types of the food, and determining the nutrient coverage according to the total number of nutrient types;

[0086] Step S220, obtaining the number of first nutrient types of the food according to the first screening standard, and determining the nutrient density according to the number of the first nutrient types;

[0087] Among them, the nutritional characteristic values ​​include: the nutritional coverage and the nutrient density; the first screening criterion is to select a number of nutrients whose actual content is greater than or equal to a preset first standard content.

[0088] Specifically, in this embodiment, the nutrient coverage K1 is calculated based on the total nutrient type number X0 combined with the total nutrient type number X0';

[0089] K1=X0 / X0';

[0090] Calculating the nutrient density K2 according to the first nutrient type number X1 combined with the total nutrient type number X0;

[0091] K2=X1 / X0;

[0092] For example:

[0093] The total nutrients corresponding to a certain diet include: protein, vitamin A, vitamin B, carbohydrates; the corresponding first nutrients include: protein and carbohydrates;

[0094] The number of types of total nutrients X0' in this embodiment is 10;

[0095] Then the nutritional coverage K1=X0 / X0'=4 / 10;

[0096] The nutrient density K2=X1 / X0=2 / 4;

[0097] In this embodiment, the total nutrient type number X0' represents all chemical substances in various foods that can provide energy or support body functions; the total nutrient type number X0 represents all chemical substances included in a food that can provide energy or support body functions; wherein X0≤X0'; X1≤X0;

[0098] For example, the types of total nutrients include: protein, carbohydrates, fat, dietary fiber, vitamins, minerals, water, etc.; for a certain food U, the total nutrient types corresponding to the food U include: protein, fat, vitamins, minerals, water;

[0099] In this embodiment, the first standard content is set to 3.2 g / 100 g; the second standard content is set to 22 g / 100 g; the specific settings are also affected by the food attributes and nutrient types; for example: for nutrients such as dietary fiber, the content of dietary fiber in food is usually very small, and dietary fiber is mainly found in foods with the attributes of whole grains, beans, vegetables, fruits and nuts; therefore, the setting values ​​of the first standard content and the second standard content of the attribute food data set for this attribute should be lower.

[0100] Specifically, by calculating the nutritional coverage, the embodiments of the present invention can understand the number of types of chemical substances contained in food that can provide energy or support body functions, which helps to judge the nutritional diversity of food; by calculating the nutrient density, the relationship between the content of specific nutrients in food and the total number of nutrient types can be understood, which helps to judge the richness of certain key nutrients in food; by setting the first standard content and the second standard content, food can be screened in a standardized manner to ensure the fairness and consistency of the evaluation; considering the influence of food properties and nutrient types, the nutritional characteristic values ​​of different foods can be more accurately evaluated; by analyzing these nutritional characteristic values ​​of food, a healthy diet can be better planned to ensure adequate nutrient intake while avoiding over or undernutrition.

[0101] See also Figure 2 As shown, it is a flow chart for generating an energy sequence, wherein the process of sorting each food in the attribute food data set according to each determined nutritional characteristic value to obtain an energy sequence includes:

[0102] Step S310, determining the number of items in the nutrient coverage and the nutrient density that meet a single determination condition;

[0103] Step S320, determining the energy levels of various foods according to the number of items, and grading and classifying the various foods according to the energy levels to obtain a plurality of food data groups;

[0104] Step S330, based on the classification result, calculate the initial energy score of each food according to the nutrient coverage and the nutrient density, and sort the various foods in each food data group according to the initial energy score;

[0105] Step S340, integrating the primary sorting results in each food data group to obtain the primary energy sequence;

[0106] Among them, the initial energy score = nutritional coverage + nutrient density.

[0107] Specifically, the process of determining the number of items in the nutrient coverage and the nutrient density that meet a single determination condition in this embodiment includes:

[0108] Determining whether the nutrient coverage meets the single determination condition according to the total number of nutrient types and a preset first evaluation value;

[0109] Determining whether the nutrient density meets the single determination condition according to the number of the first nutrient types and a preset second evaluation value;

[0110] Wherein, based on the total number of nutrient types being greater than or equal to the first evaluation value, it is determined that the nutrient coverage meets the single determination condition; based on the total number of nutrient types being less than the first evaluation value, it is determined that the nutrient coverage does not meet the single determination condition;

[0111] Based on the number of the first nutrient types being greater than or equal to the second evaluation value, it is determined that the nutrient density meets the single determination condition; based on the number of the first nutrient types being less than the second evaluation value, it is determined that the nutrient density does not meet the single determination condition;

[0112] In this embodiment, the first evaluation value is set to 4; the second evaluation value is set to 1-3; and selective adaptive adjustment is performed according to food attributes and nutrient types.

[0113] See also Figure 3 As shown, it is an energy level determination logic diagram, wherein the process of determining the energy level of various foods according to the number of items, and grading and classifying various foods according to the energy level to obtain a plurality of food data groups includes:

[0114] For any kind of food, when the number of items is 2, the energy level is determined to be level one; when the number of items is 1, the energy level is determined to be level two; when the number of items is 0, the energy level is determined to be level three;

[0115] Various foods are graded and divided according to the graded and divided results to obtain a primary food data group, a secondary food data group and a tertiary food data group.

[0116] Specifically, the embodiments of the present invention can evaluate the energy level of food by judging the number of items that meet a single judgment condition in the nutritional coverage and nutrient density, which helps to identify foods of different energy levels; various foods are graded and divided according to the energy level to obtain food data groups of different energy levels, which helps to classify and analyze the food more carefully; based on the nutritional coverage and nutrient density, the initial energy scores of various foods are calculated, and the foods are sorted according to the scores, which helps to more accurately evaluate the energy value of the food; the primary sorting results in each food data group are integrated to obtain an energy sequence, which helps to comprehensively evaluate and compare the food; according to the energy level and energy score of the food, a healthy diet can be planned to ensure the intake of an appropriate amount of energy while avoiding excessive or insufficient energy intake; by quantifying the intrinsic energy characteristics of the food, it helps to more scientifically and accurately evaluate the energy value of the food.

[0117] Specifically, the process of labeling various foods with a corresponding type of energy according to the analysis results in this embodiment includes:

[0118] Step S510, for any main nutrient component data string, obtaining the number of main nutrient types in the main nutrient component data string;

[0119] Step S520, marking the food corresponding to the main nutrient component data string with a type of energy according to the number of types of the main nutrients.

[0120] Specifically, the process of marking the food corresponding to the main nutrient component data string with a type of energy according to the number of main nutrient types in this embodiment includes:

[0121] If the number of main nutrients is equal to 0, the food is not marked;

[0122] Based on the number of main nutrient types being equal to 1, the food is labeled as: single type;

[0123] Based on the number of the main nutrients being greater than 1, obtaining the main content of each main nutrient;

[0124] According to each main content combined with the second standard content, a type of energy labeling is determined as a composite type, or a biased type.

[0125] Specifically, the process of determining a type of energy labeling as a composite type or a biased type according to each main content combined with the second standard content in this embodiment includes:

[0126] Calculate the content difference between each main content and the second standard content;

[0127] Determining a difference ratio according to the content difference and a preset third evaluation value;

[0128] Based on the difference ratio not being 0, it is determined that the energy label type of the food is the composite type;

[0129] Based on the difference ratio being 0, determining that the energy label type of the food is the biased type;

[0130] For any main content, calculate the content difference corresponding to the main content;

[0131] The content difference = main content - second standard content; in this embodiment, the main content is greater than or equal to the second standard content;

[0132] If the content difference is greater than or equal to the third evaluation value, the nutrient corresponding to the main content is determined to be a macronutrient;

[0133] If the content difference is less than the third evaluation value, it is determined that the nutrient corresponding to the main content is a micronutrient;

[0134] Obtaining the amount of the macronutrient to obtain the macro number; obtaining the amount of the micronutrient to obtain the micro number;

[0135] Calculating a difference ratio according to the macro number and the micro number;

[0136] When the number of macro-amounts is greater than or equal to the number of trace-amounts, the difference ratio = the number of trace-amounts / the number of macro-amounts;

[0137] When the number of macro-amounts is less than the number of micro-amounts, the difference ratio = the number of macro-amounts / the number of micro-amounts;

[0138] If the difference ratio is equal to 0, it is determined that the energy label type of the food is the biased type;

[0139] If the difference ratio is not equal to 0, it is determined that the energy label type of the food is the composite type;

[0140] In this embodiment, the third evaluation value is set to 4 / 100; the specific setting is also affected by food properties and nutrient types.

[0141] Specifically, the embodiment of the present invention realizes the refined classification of food by judging the number of types of main nutrients in food; it not only helps to understand the nutritional composition of food more clearly, but also guides healthier dietary choices; for example, a single type of food may be more suitable for people with specific dietary needs, while compound or biased types of food can provide more comprehensive nutrition; by calculating the difference between the content of each main nutrient and the second standard content, and combining the preset third evaluation value to determine the macro or trace classification of the nutrient, this method is scientific and objective; it avoids errors caused by subjective judgment, making energy labeling more accurate and reliable; by energy labeling of food, a healthy diet can be better planned to ensure the intake of appropriate amounts of nutrients while avoiding overnutrition or undernutrition; the main nutrients of each food are quantified and analyzed, and their nutrient types and contents are marked, making the nutritional components of the food more transparent.

[0142] See also Figure 4 As shown, it is a flow chart of the second type of energy labeling, wherein the process of labeling various foods with the second type of energy according to the energy density level and the expansion level includes:

[0143] Step S610, for any kind of food, obtaining the actual energy content and target nutrients of the food;

[0144] Step S620, determining the energy density level as low energy density, medium energy density or high energy density according to the actual energy content;

[0145] Step S630, determining the expansion degree level as low expansion degree, medium expansion degree or high expansion degree according to the target nutrient;

[0146] Step S640: determining the second energy labeling type of various foods as A-type food, B-type food, and C-type food based on the energy density level and the degree of expansion level.

[0147] In this embodiment, the actual energy content refers to the energy contained in the food per unit mass (per 100 grams), which is used to measure the energy content of the food.

[0148] For example: For a food, the total nutrients of the food include: carbohydrates, proteins and fats;

[0149] 1. Determine the total energy of the food:

[0150] Carbohydrates: Each gram provides 4 kcal of energy;

[0151] Protein: Each gram provides 4 kcal of energy;

[0152] Fat: Each gram provides 9 kcal of energy.

[0153] 2. Calculate the energy per 100 grams of food: multiply the energy of each nutrient in the food by its weight percentage in the food, and then add up the energy of all nutrients;

[0154] Assume that the total weight of the food is 100 grams, which contains:

[0155] Carbohydrates: 40 g;

[0156] Protein: 10 g;

[0157] Fat: 20 g;

[0158] Carbohydrate energy: 40 g x 4 kcal / g = 160 kcal;

[0159] Protein energy: 10 g x 4 kcal / g = 40 kcal;

[0160] Fat energy: 20 g x 9 kcal / g = 180 kcal;

[0161] Then the actual energy content = 160 kcal + 40 kcal + 180 kcal = 380 kcal.

[0162] 3. Determine energy density: Divide the total energy of the food by the total weight of the food to get the energy density per 100 grams of food;

[0163] The energy density is = total energy / total weight = 380 kcal / 100 g = 3.8 kcal / g.

[0164] Calculating the absolute value of the energy density difference according to the energy density and a preset standard density;

[0165] The absolute value of the energy density difference=|energy density-standard density|;

[0166] Determining the energy density level according to the absolute value of the energy density difference combined with a preset fourth evaluation value;

[0167] If the absolute value of the energy density difference is less than or equal to the fourth evaluation value, the energy density level is determined to be the medium energy density;

[0168] If the absolute value of the energy density difference is greater than the fourth evaluation value and the energy density is less than the standard density, determining that the energy density level is the low energy density;

[0169] If the absolute value of the energy density difference is greater than the fourth evaluation value and the energy density is greater than the standard density, determining that the energy density level is the high energy density;

[0170] In this embodiment, the standard density is set to 2.8 kcal / g; the fourth evaluation value is set to 1.5;

[0171] In this embodiment, the target nutrients include: dietary fiber, protein, and water; since dietary fiber is a non-starch polysaccharide, it can increase the volume of food, slow down the gastric emptying rate, and thus increase the swelling degree, so high-fiber foods usually have a higher swelling degree; protein digestion is slow, and can provide a more lasting swelling degree, so high-protein foods also usually have a higher swelling degree; foods with high water content, such as fruits and vegetables, can quickly fill the stomach and provide a short-term swelling degree;

[0172] Obtaining dietary fiber content, protein content, and water content of the food according to the target nutrients;

[0173] Calculating swelling strength according to the dietary fiber content, the protein content, and the moisture content;

[0174] The swelling strength = (dietary fiber content × d1) + (protein content × d2) + (water content × d3);

[0175] Wherein, d1 is the first calculation compensation parameter of dietary fiber content to the swelling strength; d2 is the second calculation compensation parameter of protein content to the swelling strength; d3 is the third calculation compensation parameter of moisture content to the swelling strength; in this embodiment, the first calculation compensation parameter d1 is set to 2; the second calculation compensation parameter d2 is set to 0.5; the third calculation compensation parameter d3 is set to 0.02;

[0176] For example, if a food has a dietary fiber content of 5 g / 100 g, a protein content of 10 g / 100 g, and a water content of 80 g / 100 g;

[0177] Then the expansion strength = (5×2) + (10×0.5) + (80×0.02) = 10 + 5 + 1.6 = 16.6;

[0178] Calculating an absolute value of a strength difference according to the expansion strength and a preset standard strength;

[0179] The absolute value of the strength difference=|expansion strength-standard strength|;

[0180] Determining the expansion degree level according to the absolute value of the strength difference and a preset fifth evaluation value;

[0181] If the absolute value of the intensity difference is less than or equal to the fifth evaluation value, the energy density level is determined to be the medium expansion degree;

[0182] If the absolute value of the intensity difference is greater than the fifth evaluation value and the expansion intensity is less than the standard intensity, determining that the energy density level is the low expansion degree;

[0183] If the absolute value of the intensity difference is greater than the fifth evaluation value and the expansion intensity is greater than the standard intensity, determining that the energy density level is the high expansion degree;

[0184] In this embodiment, the standard intensity is set to 20-25; the fifth evaluation value is set to 3-5; and selective adaptation adjustment is performed according to the food attributes;

[0185] Determine the second energy label type of various foods as A-type food, B-type food, and C-type food based on the energy density level and the expansion degree level;

[0186] Category A foods (high expansion / low energy density);

[0187] B foods (medium bulking / medium energy density);

[0188] Category C foods (low expansion / high energy density).

[0189] Specifically, the embodiments of the present invention can understand the energy contained in each unit weight of food by calculating energy density, which is helpful to judge the energy content of food; by calculating expansion intensity, the expansion degree of food during digestion can be understood, which is helpful to judge the nutritional characteristics and energy type of food; according to the energy density level and expansion level, food can be marked as Class A, Class B or Class C, which helps to distinguish different types of food, thereby guiding the selection and matching of food; by analyzing the energy density level and expansion level of food, a healthy diet can be better planned to ensure the intake of an appropriate amount of energy while avoiding excessive or insufficient energy intake; by comprehensively considering the actual energy content and target nutrients of food, the energy density and expansion level of food can be comprehensively evaluated; a comprehensive evaluation helps to understand the nutritional value of food more accurately; according to the energy density and expansion level, food is divided into Class A, Class B and Class C, and this classification method is both scientific and practical; it can meet the expansion degree without causing excessive energy intake, and help choose a healthier diet, thereby preventing obesity and related diseases.

[0190] Specifically, the process of correcting the primary energy sequence and adding a mark stamp based on the first energy marking result and the second energy marking result in this embodiment to obtain the actual energy sequence table includes:

[0191] Step S710, screening the attribute food data set based on the first energy labeling result and the second energy labeling result to obtain a labeled food data cluster;

[0192] Step S720, identifying the marked food data cluster to determine the actual marked species and actual marked types of various foods;

[0193] Step S730, correcting the initial energy scores of various foods according to the actual marking types and the actual marking types to obtain actual energy scores;

[0194] Step S740: re-sorting the primary energy sequence based on the actual energy score to obtain an actual energy sequence, and adding the mark stamp to the actual energy sequence based on the first-category energy marking result and the second-category energy marking result to obtain the actual energy sequence table.

[0195] Specifically, in this embodiment, the marked food data cluster is identified, and for any food in the marked food data cluster;

[0196] If the actual marking type of the food is 2, that is, the food carries both a Class I energy mark and a Class II energy mark; and according to the actual marking type, the Class I energy mark result of the food is determined to be: the composite type; and the Class II energy mark result is: Class A food; then it is determined to start the correction mode;

[0197] Correcting the initial energy score of the food according to the correction mode to obtain the actual energy score;

[0198] The actual energy score = (nutrient coverage + nutrient density) × h;

[0199] Wherein, h is a correction adjustment parameter for the actual energy score; in this embodiment, the correction adjustment parameter is set to 1.5.

[0200] Specifically, the embodiment of the present invention can more comprehensively evaluate the actual energy value of food by combining Class I energy labels and Class II energy labels; the comprehensive evaluation method improves the accuracy and scientificity of energy evaluation; for foods with both Class I energy labels and Class II energy labels, the correction mode can be turned on to correct the initial energy score according to the specific attributes of the food; the energy score is made closer to the actual nutritional value of the food, which helps to make more reasonable dietary choices; based on the corrected actual energy score, the primary energy sequence is re-sorted to obtain the actual energy sequence, making the energy sequence more reasonable and able to more accurately reflect the energy differences between foods; on the basis of the actual energy sequence, mark stamps are added according to the results of Class I and Class II energy marking to form an actual energy sequence table; the marking method enhances the transparency of information, so that the nutritional characteristics and energy value of food can be understood more intuitively.

[0201] Specifically, the acquisition period in this embodiment is set to one week. Within the preset acquisition period, various physiological parameters and health indicators of the personnel to be optimized are collected, and the collected parameter information is sorted to ensure the accuracy and completeness of the data;

[0202] Select a linear regression model that can accurately predict the direction of health progress of the personnel to be optimized; input the sorted parameters of the personnel to be optimized as input variables into the linear regression model;

[0203] The linear regression model calculates the actual progress direction of the personnel to be optimized based on the input parameters through internal algorithms;

[0204] The progress direction in this embodiment may be a specific value (such as a weight change), a trend (such as a weight loss trend) or a classification result (such as health improvement, maintenance or deterioration); this embodiment does not make specific limitations;

[0205] The actual progress direction output by the linear regression model is combined with the actual energy sequence table to output the dietary energy prediction result;

[0206] In this embodiment, the dietary energy prediction result can be a specific dietary plan, including the types, quantities and proportions of food to be consumed daily; it can also be a suggestive guidance, such as increasing the intake of certain nutrients, reducing the intake of certain foods, etc. This embodiment does not make specific limitations.

[0207] Specifically, the embodiment of the present invention ensures the timeliness and dynamism of data by setting the acquisition cycle to one week; high-frequency data collection enables health management to respond more quickly to changes in the physical condition of the person to be optimized, thereby adjusting the dietary plan and other health intervention measures in a timely manner; through a strict data collation and verification process, the accuracy and completeness of the parameter information input into the linear regression model are ensured; the accuracy of the model prediction is improved, making the output actual progress direction and dietary energy prediction results more reliable; the linear regression model is used to predict the direction of health progress, combining the personalized physiological parameters and health indicators of the person to be optimized; the prediction method can more accurately reflect the health status and change trend of the person to be optimized, and provide strong support for subsequent dietary planning; the actual progress direction is combined with the actual energy sequence table, and the nutritional value and health benefits of food are comprehensively considered; the comprehensive evaluation method makes the dietary energy prediction results more comprehensive and scientific, and provides personalized dietary plans or advisory guidance for the person to be optimized; through regular monitoring, prediction and adjustment of dietary plans, the continuous health management process helps to promote the improvement of the overall health status of the person to be optimized.

[0208] The calculation compensation parameters and the calculation adjustment parameters described in the present invention have two functions: one is to balance the left and right dimensions of the formula, and the other is to adjust the numerical results. No specific assignment is performed in this embodiment. In addition, the calculation formulas in this embodiment are used to intuitively reflect the adjustment relationship between the numerical values, such as positive correlation and negative correlation. Unless otherwise specified, the parameter values ​​that are not specifically limited to numerical values ​​are all positive.

[0209] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0210] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing dietary energy intake for obese people, characterized in that: include: Based on the food information database, preliminary classification is performed according to food attributes to obtain food data sets with different attributes; For any attribute food data set, obtain the nutrient content sequence of various foods in the attribute food data set, identify the nutrient content sequence, and determine the nutrient characteristic values ​​of various foods; Sorting each food in the attribute food data set according to each determined nutritional characteristic value to obtain an energy sequence; Select nutrients from the nutrient content sequence according to the second screening standard to obtain main nutrient content data strings of various foods; Analyze the data strings of each main nutrient component, and assign a corresponding energy label to each food according to the analysis results; Determining the energy density level and the expansion level of various foods according to the nutrient content sequence, and performing corresponding second-class energy labeling on various foods according to the energy density level and the expansion level; The specific process of determining the expansion degree level includes: obtaining the dietary fiber content, protein content and water content of the food based on the target nutrients of the food, determining the expansion strength according to the dietary fiber content, the protein content and the water content combined with the calculation compensation parameters set corresponding to each content, and determining the expansion degree level according to the expansion strength combined with the preset standard strength; Based on the first-class energy marking result and the second-class energy marking result, the primary energy sequence is corrected and a marking stamp is added to obtain an actual energy sequence table; According to a preset acquisition cycle, periodically acquire the parameters of the personnel to be optimized, and input the parameters of the personnel to be optimized into a linear regression model to output the actual progress direction; Combining the actual energy sequence table, the first type of energy labeling result and the second type of energy labeling result according to the actual progress direction to output a dietary energy prediction result; Wherein, the second screening standard is to select a number of nutrients whose actual content is greater than or equal to a preset second standard content; The process of identifying the nutrient content sequence to determine the nutrient characteristic values ​​of various foods includes: For any kind of food, the total number of nutrient types of the food is obtained, and the nutrient coverage is determined according to the total number of nutrient types; Obtaining the number of first nutrient types of the food according to the first screening standard, and determining the nutrient density according to the number of the first nutrient types; Among them, the nutritional characteristic values ​​include: the nutritional coverage and the nutrient density; the first screening criterion is to select a number of nutrients whose actual content is greater than or equal to a preset first standard content.

2. The method for optimizing dietary energy intake for obese people according to claim 1, characterized in that: The process of sorting the foods in the attribute food data set according to the determined nutritional characteristic values ​​to obtain an energy sequence includes: Determining the number of items in the nutrient coverage and the nutrient density that meet a single determination condition; Determining the energy level of various foods according to the number of items, and grading and classifying various foods according to the energy level to obtain a plurality of food data groups; Based on the classification results, the initial energy scores of various foods are calculated according to the nutrient coverage and the nutrient density, and various foods in each food data group are sorted according to the initial energy scores; The primary sorting results in each food data group are integrated to obtain the primary energy sequence.

3. The method for optimizing dietary energy intake for obese people according to claim 2, characterized in that: The process of determining the number of items in the nutrient coverage and the nutrient density that meet a single determination condition includes: Determining whether the nutrient coverage meets the single determination condition according to the total number of nutrient types and a preset first evaluation value; Determining whether the nutrient density meets the single determination condition according to the number of the first nutrient types and a preset second evaluation value; Wherein, based on the total number of nutrient types being greater than or equal to the first evaluation value, it is determined that the nutrient coverage meets the single determination condition; based on the total number of nutrient types being less than the first evaluation value, it is determined that the nutrient coverage does not meet the single determination condition; Based on the fact that the number of the first nutrient types is greater than or equal to the second evaluation value, it is determined that the nutrient density meets the single determination condition; based on the fact that the number of the first nutrient types is less than the second evaluation value, it is determined that the nutrient density does not meet the single determination condition.

4. The method for optimizing dietary energy intake for obese people according to claim 3, characterized in that: The process of determining the energy level of various foods according to the number of items, and grading and classifying various foods according to the energy level to obtain a plurality of food data groups includes: For any kind of food, when the number of items is 2, the energy level is determined to be level one; when the number of items is 1, the energy level is determined to be level two; when the number of items is 0, the energy level is determined to be level three; Various foods are graded and divided according to the graded and divided results to obtain a primary food data group, a secondary food data group and a tertiary food data group.

5. The method for optimizing dietary energy intake for obese people according to claim 4, characterized in that: The process of labeling various foods with a corresponding type of energy according to the analysis results includes: For any main nutrient component data string, obtain the number of main nutrient types in the main nutrient component data string; The food corresponding to the main nutrient component data string is marked with a type of energy according to the number of types of the main nutrients.

6. The method for optimizing dietary energy intake for obese people according to claim 5, characterized in that: The process of marking the food corresponding to the main nutrient component data string with a type of energy according to the number of the main nutrient types includes: If the number of main nutrients is equal to 0, the food is not marked; Based on the number of main nutrient types being equal to 1, the food is labeled as: single type; Based on the number of the main nutrients being greater than 1, obtaining the main content of each main nutrient; According to each main content combined with the second standard content, a type of energy labeling is determined as a composite type, or a biased type.

7. The method for optimizing dietary energy intake for obese people according to claim 6, characterized in that: The process of determining a type of energy labeling as a composite type or a biased type according to each main content combined with the second standard content includes: Calculate the content difference between each main content and the second standard content; Determining a difference ratio according to the content difference and a preset third evaluation value; Based on the difference ratio not being 0, it is determined that the energy label type of the food is the composite type; Based on the difference ratio being 0, it is determined that the energy label type of the food is the biased type.

8. The method for optimizing dietary energy intake for obese people according to claim 7, characterized in that: The process of labeling various foods with corresponding second-class energy according to the energy density level and the expansion level includes: For any food, obtain the actual energy content and target nutrients of the food; Determining the energy density level as low energy density, medium energy density or high energy density according to the actual energy content; Determining the overswelling level as low overswelling, medium overswelling or high overswelling according to the target nutrient; The secondary energy label type of each food is determined based on the energy density level and the overrun level.

9. The method for optimizing dietary energy intake for obese people according to claim 8, characterized in that: The process of correcting the primary energy sequence and adding a mark stamp based on the first-class energy marking result and the second-class energy marking result to obtain an actual energy sequence table includes: The attribute food data set is screened based on the first energy labeling result and the second energy labeling result to obtain a labeled food data cluster; Identifying the labeled food data clusters to determine the actual labeled categories and actual labeled types of various foods; Correcting the initial energy scores of various foods according to the actual marking categories and the actual marking types to obtain actual energy scores; The primary energy sequence is reordered based on the actual energy score to obtain an actual energy sequence, and the mark stamp is added to the actual energy sequence based on the first type of energy marking result and the second type of energy marking result to obtain the actual energy sequence table.

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