TW201807654A - Customized nutrition management system, processing method thereof and application program and storing media using the same - Google Patents

Abstract

A customized nutrition management system is disclosed, which comprises a storing unit and a processing unit. The storing unit comprises a case information, a nutrient intake criteria database having a nutrient intake criteria information, a nutrient index database recording a correspondence between a nutrient discrepancy and a discrepancy index, and a proposal database recording a correspondence between a main index and a resolution proposal. The processing unit comprises a discrepancy analysis unit, an index generation unit and a proposal generation unit. The discrepancy analysis unit produce a discrepancy analysis unit by means of comparing the case information with the nutrient criteria information. The index generation unit receives the nutrient discrepancy produced by the discrepancy analysis unit, and generates a discrepancy index according to the received nutrient discrepancy corresponding to the nutrient index database. The discrepancy index is defined as a first main index. The proposal generation unit receives the first main index generated by the index generation unit, and produces a first resolution proposal according to the first main index corresponding to the proposal database.

Description

Customized nutrition management system and its processing method, application program and storage medium

The invention relates to a nutrition management system and a processing method and application thereof, and in particular to a nutrition management system customized according to a user, a processing method thereof, an application program and a storage medium.

Although most of the foods in daily life are labeled with nutrients (such as calories, protein, fat, saturated fat, trans fats, carbohydrates, etc.), consumers often do not rely on their own health, exercise, body Diseases and other conditions, recording their own eating habits and intake of nutrients, resulting in imbalanced nutritional intake (partial overnutrition, partial nutrition is insufficient). Even if the consumer adjusts the diet based on the dietary intake of dietary nutrients announced by the Ministry of Health and Welfare, it will still be affected by its own psychological factors, or some food and beverage operators may not clearly identify the nutrients of the food, and cannot effectively manage the nutritional intake.

An embodiment of the present invention discloses a customized nutrition management system including a storage unit and a processing device connected to the storage unit, wherein the storage unit includes at least one case data, and a nutrition including at least one nutritional intake reference material. The ingestion benchmark database, a database of nutritional indicators that record a correspondence between nutritional differences and heterogeneous indicators, and a program database that records a correspondence between major indicators and solutions. The processing device includes an abnormality analyzing unit, an indicator generating unit and a plan generating unit, wherein the abnormal analyzing unit compares the case data with the nutritional intake reference data to generate a nutritional difference, and the indicator generating unit receives the abnormality And analyzing the nutritional difference generated by the unit, and generating at least one abnormality indicator according to the nutritional difference received, wherein the abnormality indicator is defined as a first major indicator, and the program is generated The unit receives the first primary indicator generated by the indicator generating unit, and generates at least one first solution according to the first primary indicator corresponding to the solution database.

An embodiment of the present invention discloses a method for processing a customized nutrition management system, comprising: comparing a case data with a nutrient intake reference data to generate a nutritional difference, wherein the nutrient intake reference data is stored in the customized nutrition a nutrition intake reference database of the management system; generating, according to the nutritional difference, a correspondence between a nutritional difference and an abnormality indicator to generate at least one abnormality indicator, wherein the abnormality indicator is defined as a first primary indicator The correspondence between the nutritional difference and the abnormality indicator is stored in a nutrition index database of the customized nutrition management system; and corresponding to the correspondence between a main indicator and the solution according to the first main indicator To generate at least a first solution, wherein the correspondence between the main indicator and the solution is stored in a solution database of the customized nutrition management system.

One embodiment of the present invention discloses an application of a customized nutrition management system that can be executed in a computer system to perform the aforementioned processing methods.

An embodiment of the present invention discloses a storage medium storing a customized nutrition management system instruction set, and the step of loading the computer system to perform the foregoing processing method.

Please refer to FIG. 1 , which is a block diagram of a customized nutrition management system according to an embodiment of the invention. As shown in FIG. 1 , the customized nutrition management system 10 includes a data input and output interface 100 , a storage unit 106 connected to the data input and output interface 100 , and a processing device 102 connected to the data input and output interface 100 and the storage unit 106 . .

The data input and output interface 100 provides a user to input a case data and questionnaire data by using an input device such as a keyboard, a mouse, a touch screen, and the like, and output at least one main index on the output device such as a screen or a speaker, and the main indicator Provide an interactive menu interface. The case data and the questionnaire data are stored in the storage unit 106 for processing and use by the processing device 102.

The processing device 102 is, for example, a computer processor (CPU) or a microprocessor (μP), and includes a food conversion unit 1030, a heterogeneous analysis unit 1022 connected to the food conversion unit 1030, and a different cause analysis unit 1024. An indicator generating unit 1026 connected to the heterogeneous analyzing unit 1022 and the dissimilarity analyzing unit 1024 and a scheme generating unit 1028 connected to the index generating unit 1026 will be described later in detail with respect to the operations of the units.

The storage unit 106 is, for example, a memory, a hard disk, a compact disk, a cloud storage space, a media storage system, etc., and includes an application of a customized nutrition management system, a customized nutrition management system instruction set, and/or various databases. The type of the database includes the program database D8 shown in Figure 2 (or Figure 6), the food nutrition database D1 shown in Figure 3, the nutritional index database D2, and the nutritional intake reference database D3, Figure 4 The questionnaire database D6, the behavior benchmark database D4, and the behavior indicator database D5 shown in the figure, and/or the big data database D7 of FIG. 6 will be explained in detail below.

In another embodiment, the customized nutrition management system 10 further includes an external data import unit 108, which is a platform interface or communication for providing input, expansion or update of the food nutrition database D1. Equipment, etc.

2 is a flow chart showing a processing method of a customized nutrition management system according to an embodiment of the invention. Referring to FIG. 1 and FIG. 2 simultaneously, in step S10, the data output interface 100 receives case data, including personal consultation reasons and problems, living diet and medication habits, personal medical history and family medical history, and body position data (eg, Height, weight, BMI, body fat, waist circumference and hip circumference, etc.), exercise data (such as exercise, most frequently exercised, exercise frequency, etc.), biochemical data (such as blood sodium, blood potassium, blood red) Vegetarian, etc.) and daily diet content. In step S20, the abnormality analyzing unit 1022 of the processing device 102 refers to the body position data, the biochemical data, the daily diet content, and the like in the received case data, and refers to the food nutrition database D1 and the nutrition index database D2 shown in FIG. 3 . The nutrient intake benchmark database D3 cross-analyzed at least one abnormality indicator. In step S30, the dissimilarity analysis unit 1024 of the processing device 102 analyzes at least the questionnaire data in the received case data and refers to the questionnaire database D6, the behavior reference database D4, and the behavior indicator database D5 shown in FIG. An indicator of difference. In step S40, the indicator generating unit 1026 of the processing device 102 performs a cross-analysis operation according to the aforesaid abnormality index and the heterogeneous index to generate at least one final primary indicator and/or at least one ranked primary indicator. In step S60, the solution generation unit 1028 of the processing device 102 obtains at least one solution according to the foregoing final main indicator and/or a ranked main indicator corresponding to the solution database D8. The solution database D8 includes a plurality of pen solutions, and the correspondence between the main indicators and the solution may be recorded in the form of a lookup table, and the correspondence between the main indicators and the solutions may be one-to-one. A relationship or a one-to-many relationship, that is, a primary indicator corresponds to at least one solution. In another embodiment, depending on the design of the system or the needs of the user, the primary indicator KI may also be the abnormal indicator A1 or the heterogeneous indicator A2, and the two may be independently presented.

FIG. 3 is a specific flowchart of the generation of the abnormality indicator A1 of step S20 of FIG. 2 . The abnormality index A1 is a reference for providing an abnormality in the intake. Referring to FIG. 1, FIG. 2 and FIG. 3, the user A inputs the above-mentioned case data I in the data input/output interface 100 of FIG. 1, and displays the data of the following Table 1 in the data output interface 100. Table 1

In step S202, the abnormality analyzing unit 1022 of the processing device 102 calculates a person's actual nutritional intake based on the daily diet content in the case data I and corresponding to the reference food nutrition database D1, for example, calculating how much heat a person has in a day's diet. Nutritional ingredients such as protein, fat, etc. The ingredient nutrition database D1 includes the nutrients of each ingredient, food, health food, such as the nutrient label covered by 100 grams of rice starch powder, 61 calories, 0.6 grams of protein, 0.5 grams of fat, 120 grams of saturated fat. The information may be provided by the food product manufacturer, the health food supplier or the restaurant in the storage unit 106. The data may be initially built in the storage unit 106 or may be received through the external data import unit 108 of FIG. Store, update, or expand. The data of the calories, protein, fat, saturated fat, etc. of the stick legs are calculated by taking one of the stick legs in the above Table 1 as an example corresponding to the food nutrition database D1.

Next, in step S204, the abnormality analyzing unit 1022 analyzes the nutritional intake reference data in the actual intake nutritional result and the nutritional intake reference database D3 of the individual to analyze a nutritional difference, wherein the nutritional difference may include a difference value or further calculation The magnitude of the difference value is obtained. At least one nutrient intake benchmark data is recorded in the aforementioned nutrient intake benchmark database D3, and the nutrient intake benchmark data may be the reference amount of the human nutrient referenced by the Ministry of Health and Welfare, the reference material published by the American Nutritional Diet Association (ADA) or any world. The reference materials published by the sex organization, or the formula reference materials calculated based on the body position data and biochemical data of the case, or the reference materials obtained by mixing the case data according to the reference materials published by each unit. Taking the calorie intake benchmark data as an example, it is possible to obtain the recommended reference calorie by averaging the actual intake of nutritional results of the individual case with the reference materials published by each unit and the formula reference data of the case, assuming the actual calorie deduction of the case is recommended. After the heat is greater than 30% of the recommended reference heat, it means that there is a nutritional difference. When it is determined in step S204 that there is a nutritional difference, the process proceeds to step S206. When it is judged in step S204 that no nutrient difference is generated, the flow of this phase is ended.

In step S206, the indicator generating unit 1026 generates the abnormal indicator A1 on the data input and output interface 100 according to the nutritional difference generated in step S204 corresponding to the nutritional index database D2, wherein the nutritional indicator database D2 includes at least one nutritional indicator data. The correspondence between the nutritional difference and the abnormality index can be recorded in the form of a lookup table. Taking the aforementioned heat as an example, the nutrient difference generated by the heat corresponds to the nutritional index data of the nutrition index database D2, and the generated abnormality index A1 is excessive heat intake.

In another embodiment, the nutritional difference comparison in step S204 does not necessarily depend on the actual intake of the nutritional result calculated by the individual in step S202. If the comparison object is other information of the case data, such as the BMI of the body position data (weight/height) The squared or IBW (ideal weight) is based on the nutrient intake baseline data in the Nutritional Intake Reference Library D3 (BMI less than or equal to 24 or IBW% less than or equal to 115%), if the case data has a BMI greater than 24 or IBW% greater than 115 , it will produce a nutritional difference. In step S206, the indicator generating unit 1026 generates the abnormal indicator A1 on the data input and output interface 100 according to the nutritional difference generated in step S204 corresponding to the nutritional index database D2, taking the aforementioned BMI and IBW as an example, and the nutritional difference corresponds to The resulting abnormality is referred to as being overweight.

FIG. 4 is a specific flowchart of generating the dissimilarity indicator A2 of step S30 of FIG. 2 . The heterogeneity indicator is used to provide a reference for the triggering of nutritional abnormalities. Referring to FIG. 1 , FIG. 2 and FIG. 4 simultaneously, the user A inputs the foregoing questionnaire data II in the data input and output interface 100 of FIG. 1 , and the questionnaire data II includes at least one topic and at least one option corresponding to the topic, for example, The question is the frequency of food purchase. The option is to choose 1 if it is less than 1 time per week, or 10 if it is more than 5 times per week.

In step S301, the dissimilarity analysis unit 1024 of the processing device 102 calculates an actual behavior value according to the option of the questionnaire data II and corresponding to the reference questionnaire database D6. The questionnaire database D6 includes the classification corresponding to each question, such as the self-efficacy corresponding to the frequency of purchasing food, and the classification corresponding to the positive degree of changing the diet is the motivation willingness. The questionnaire database D6 also includes the topic relevance and corresponding calculation formula between each question. For example, the title 3 and the topic 5 are related, and the corresponding calculation formula is the average of the two questions, and the heterogeneous analysis unit 1024 That is, the questions 3 and 5 in the questionnaire data II are calculated according to the calculation formula in the questionnaire database D6 to obtain the actual behavior value. In another embodiment, the heterogeneous analysis unit 1024 performs the operation of the options of the same classified item, such as summing or averaging, to obtain the behavior characteristic value of each category, including the foregoing self-efficacy, motivation willingness, and the like. There will be a corresponding behavioral characteristic value that provides a reference indicator for the user in the other direction. The title of the questionnaire may be initially built into the storage unit 106 or may be further updated or expanded later.

Next, in step S302, the cause analysis unit 1024 compares the actual behavior value with the behavior reference data in the behavior reference database D4 to analyze a behavior difference. The behavioral benchmark data in the behavioral benchmark database D4 is an assessment criterion generated corresponding to the topic relevance of the questionnaire database D6, for example, the behavioral benchmark data of the topic 3 and the topic 5 is the average of the topic 3 and the topic 5, and the behavioral benchmark data. If the average value of the actual behavior value needs to be greater than or equal to a given value, if the abnormality analysis unit 1024 compares the actual behavior value to the given value, indicating that there is a behavior difference, the result of the behavior difference is output. If no, the process at this stage is ended.

In step S304, the indicator generating unit 1026 generates the cause indicator A2 on the data output interface 100 according to the behavior difference generated in step S302 corresponding to the behavior indicator database D5, wherein the behavior indicator database D5 includes behavior indicator data, which may The correspondence between the behavior difference and the heterogeneity index is recorded in the form of a lookup table. Taking the above questions 3 and 5 as examples, the calculated behavior difference corresponds to the behavior index data of the behavior index database D5, and the generated heterogeneity index A2 is “poor compliance with nutrition related recommendations”. Combining the aberrant indicator A1 (excessive calorie intake) of the above example, the heterogeneity index A2 (poor compliance with nutrition-related recommendations) can be used as a reference for triggering causes of nutritional abnormalities (excessive caloric intake).

The nutritional indicator data described in step S206 of FIG. 3 and the behavior indicator data described in step S304 of FIG. 4 may be stored in the same table to the nutritional index database, or separately stored in the nutritional index database D2 and the behavior index database D5. , no restrictions. Specifically, the steps of generating the abnormal indicator A1 in FIG. 3 and the generating the abnormality index A2 in FIG. 4 may be performed simultaneously or separately, and the specific order is not limited.

FIG. 5 is a specific flow chart showing the main indicators of the step S40 of FIG. 2, and the main indicator KI can provide a reference for the nutritionist or the individual to observe the nutritional status. Referring to FIG. 1 , FIG. 2 and FIG. 5 , the indicator generating unit 1026 of the processing device 102 receives the heterogeneous index A1 generated by the abnormality analyzing unit 1022 and the heterogeneous index A2 generated by the receiving heterogeneous analyzing unit 1024, wherein The abnormal indicator A1 will be defined as a first major indicator, and the heterogeneous indicator A2 will be defined as a second primary indicator. In step S402, the indicator generation unit 1026 performs a cross-analysis on the heterogeneous index A1 defined as the first main index and the dissimilarity index A2 defined as the second main index. Next, in step S404, the indicator generating unit 1026 generates at least one final primary indicator KI according to the cross-analysis of step S402. The cross analysis of the index generating unit 1026 includes a union operation, an intersection operation, and the like. If the cross analysis of the index generating unit 1026 is a union operation, the main index KI will be all possibilities of the abnormal index A1 and the heterogeneous index A2. If the cross-analysis of the index generating unit 1026 is an intersection operation, the main index KI is an index in which the heterogeneous index A1 and the heterogeneous index A2 overlap. Depending on the design of the system or the needs of the user, the main indicator KI may also be the abnormal indicator A1 or the heterogeneous indicator A2, and the two do not have to be cross-calculated and can be presented independently.

6 is a flow chart showing a processing method of a customized nutrition management system according to another embodiment of the present invention. The difference between FIG. 6 and FIG. 2 is that between step S40 and step S60, the indicator generating unit 1026 of FIG. 1 further performs step S50 to determine the final main indicator generated by step S40 according to the weight parameter in the big data database D7. A sorting operation is performed to generate a sorting main indicator SKI, and the sorting main indicator SKI is displayed in the data output interface 100. Among them, the big data database D7 stores the abnormal indicators and the heterogeneous indicators generated by similar cases in the past, which is the historical index. After sorting and analyzing the frequency of occurrence of these historical indicators, the sorting basis is the weight parameter.

For example, in the process steps of FIG. 5, 10 sets of main indicators KI may be obtained, and the indicator generating unit 1026 sorts the weights of the 10 main indicators KI according to the big data database D7 of FIG. 6, and the higher frequency of occurrence is preferred. Arrangement, the lower frequency of occurrence is ranked after, resulting in a sorting main indicator SKI. Therefore, the user (nutritionist or individual) can select the top ranked SKI (for example, the first six items) as the main improvement basis for the current nutritional status of the individual.

Please refer to FIG. 1 to FIG. 6 again, and the scheme main generating unit 1028 (shown in FIG. 1 ) of the processing device 102 may generate the final main index generated according to the flow of FIG. 5 or the main index of sorting generated according to the flow of FIG. 6 . At least one solution is obtained corresponding to the solution database D8. Taking the above-mentioned abnormality index A1 (too much calorie intake) as the main index KI as an example, the solution obtained by the scheme generation unit 1028 from the scheme database D8 is: 1. calorie-adjusted diet, 2. food/liquid plan, 3. Vitamin and mineral supplements, 4. Prioritization, etc. If you need to adjust the part of the diet, you can follow the process of the diet adjustment menu in the next steps, which will be further detailed below.

Referring to FIG. 1 and FIG. 3 again, the processing device 102 further includes a food conversion unit 1030. After step S202 of FIG. 3, the food conversion unit 1030 will actually take the nutritional result, that is, one day of ingestion, in step S203. Nutrients (calories, protein, fat, saturated fat, trans fat, carbohydrates, sugar, sodium, calcium, fiber, etc.) are converted into basic food types according to the nutritional formula (full roots, soy meat, low fat dairy) , vegetables, fruits, fat nuts, etc.) and their portions, wherein the nutritional calculation formula can be stored in the food nutrition database D1 of FIG. When the case is adjusted according to the aforementioned solution, the user can adjust the basic food type and its serving size or increase or decrease the food, food and health food itself. The food conversion unit 1030 also converts the adjusted information into The nutrient component is further compared by the abnormality analyzing unit 1022 to the nutrient intake reference data in step S204 to determine whether there is still a nutritional difference. After several adjustments, if the nutritional difference is reached, The adjusted foodstuff, food, and health food are the aforementioned dietary adjustment menus.

The implementation method of the customized nutrition management system of the above embodiment of the present invention may be an application program, and the processing method may be executed in a loading computer system, or may be a storage medium to store a nutrition management system. The instruction set, which can be loaded into a computer system, can perform the above processing methods. The customized nutrition management system can include a host server and a personal computer, a portable tablet or a smart phone, a cloud server, and the like.

In summary, the above embodiments of the present invention provide a customized nutrition management system, which is a simple and efficient nutrition management mode. In the above embodiments of the present invention, the user can make personal consultation questions and problems, living diet and medication habits, personal medical history and family medical history, body position data (such as height, weight, BMI, body fat, waist circumference and hip circumference, etc.) , exercise data (such as exercise, the most frequently exercised, exercise frequency, etc.), biochemical data (such as blood sodium, blood potassium, hemoglobin, etc.) and personal daily diet, and / or psychological behavior The results of the analysis at the level, and the recommendations for customized nutrition assessment. The above embodiments of the present invention can provide a measure of an individual's nutritional status or provide a platform for nutritionists and nutrition management workers to manage a client's nutritional status. The above embodiments of the present invention can also be implemented via a remote platform where the user can seek nutritional status assessments at any location.

The principles, preferred embodiments, and modes of operation of the invention have been described in the foregoing. However, the invention should not be construed as being limited to the specific embodiments discussed. Rather, the above-described embodiments are to be considered as illustrative and not restrictive, and the scope of the invention as defined by the following claims Changes are made to these embodiments.

10‧‧‧Customized Nutrition Management System

100‧‧‧data input and output interface

102‧‧‧Processing device

1022‧‧‧ Alien analysis unit

1024‧‧‧ analysing unit

1026‧‧‧ indicator generation unit

1028‧‧‧Program Generation Unit

1030‧‧‧Food Conversion Unit

106‧‧‧storage unit

108‧‧‧External data import unit

Steps S10, S20, S30, S40, S60‧‧ are the flow steps of the processing method of a customized nutrition management system according to an embodiment of the present invention.

Steps S202 to 206‧‧ are the flow steps of generating an abnormality index in the processing method of the customized nutrition management system according to an embodiment of the present invention.

Steps S301 to S304‧‧ are the flow steps of generating a dissimilarity index in the processing method of the customized nutrition management system according to an embodiment of the present invention.

Steps S402 to S404‧‧ are the process steps for generating the final main indicator in the processing method of the customized nutrition management system according to an embodiment of the present invention.

Steps S10 to S60‧‧ are the flow steps of the processing method of a customized nutrition management system according to another embodiment of the present invention.

I‧‧‧ case information

II‧‧‧ Questionnaire information

D1‧‧‧Food and Nutrition Database

D2‧‧‧ Nutrition Indicators Database

D3‧‧‧ Nutritional Intake Reference Database

D4‧‧‧ Behavioral Benchmark Database

D5‧‧‧ Behavioral Indicators Database

D6‧‧‧ Questionnaire Database

D7‧‧‧ Big Data Database

D8‧‧‧ programme database

1 is a block diagram showing a customized nutrition management system in accordance with an embodiment of the present invention.

2 is a flow chart showing a processing method of a customized nutrition management system according to an embodiment of the invention.

3 is a flow chart showing the generation of an abnormality index in a processing method of a customized nutrition management system according to an embodiment of the present invention.

FIG. 4 is a flow chart showing the generation of a dissimilarity index in a processing method of a customized nutrition management system according to an embodiment of the invention.

FIG. 5 is a schematic flow chart showing a final main indicator in a processing method of a customized nutrition management system according to an embodiment of the invention.

6 is a flow chart showing a processing method of a customized nutrition management system according to another embodiment of the present invention.

Claims (21)

A customized nutrition management system comprising: a storage unit comprising: at least one case data; a nutritional intake reference database comprising at least one nutritional intake reference data; a nutritional indicator database comprising a nutritional difference and a difference Correspondence between the indicators; and a program database, including a correspondence between the main indicators and the solution; and a processing device connected to the storage unit, comprising: an abnormal analysis unit, comparing the case data with The nutrient intake reference data is used to generate a nutritional difference; an indicator generating unit is connected to the abnormality analyzing unit to receive the nutritional difference generated by the abnormal analyzing unit, and corresponding to the nutritional indicator data according to the received nutritional difference The library generates at least one abnormality indicator, wherein the abnormality indicator is defined as a first primary indicator; and a scheme generating unit is connected to the indicator generating unit, and receives the first primary indicator generated by the indicator generating unit And will be based on The first major indicator corresponding to the program database to generate at least a first solution. For example, the customized nutrition management system described in claim 1 includes the individual's counseling reasons and problems, living diet and medication habits, personal medical history and family history, body position data, exercise data, biochemical data, and Daily diet content. The customized nutrition management system of claim 2, wherein the storage unit further comprises an ingredient nutrition database, the food nutrition database comprising at least one nutrient for each ingredient, food and/or health food. The abnormal analysis unit further calculates a person's actual nutritional result by referring to the food nutrition database according to the daily diet content in the case data. The customized nutrition management system according to claim 3, wherein the abnormal analysis unit compares the actual nutritional intake result of the individual with the nutritional intake reference data in the nutritional intake reference database to analyze the nutritional difference. . The customized nutrition management system of claim 1 or 4, wherein the nutritional difference comprises a difference value and/or a magnitude of the difference value. The customized nutrition management system of claim 1, wherein: the storage unit further comprises: at least one questionnaire data, including at least one topic and an option corresponding to the topic; a questionnaire database, including the questionnaire a topic correlation between the topic in the data and a corresponding calculation formula and a classification corresponding to the topic; a behavioral benchmark database comprising at least one behavioral benchmark data, the behavioral benchmark data is corresponding to the questionnaire database An evaluation criterion generated by the relevance of the topic; and a database of behavior indicators, including a correspondence between the behavior difference and the heterogeneity index; the processing device further includes: a heterogeneous analysis unit, which will be included in the questionnaire data The option is based on the relevance of the topic in the questionnaire database and the calculation formula to obtain an actual behavior value, and compares the actual behavior value with the behavioral benchmark data in the behavioral benchmark database to analyze a behavioral difference. And an indicator generating unit connected to the cause analysis unit, Receiving the difference in the behavior generated by the cause analysis unit, and generating at least one cause indicator according to the behavior difference database, wherein the cause indicator is defined as a second main indicator; The solution generating unit receives the second primary indicator generated by the indicator generating unit, and generates at least one second solution according to the second primary indicator corresponding to the solution database. The customized nutrition management system of claim 6, wherein the indicator generating unit further comprises a cross-analysis of the first main indicator and the second main indicator to generate at least one final main indicator. The customized nutrition management system of claim 7, wherein the cross-analysis of the indicator generating unit comprises a union operation or an intersection operation. The customized nutrition management system of claim 7, wherein the storage unit further comprises a large data database, wherein the big data database stores at least one historical indicator, and the frequency of occurrence of the historical indicator The ordering basis is a weighting parameter, wherein the indicator generating unit performs a sorting operation on the final main index according to the weight parameter in the big data database to generate a sorting main indicator, wherein the generating unit At least one third solution is obtained according to the ranking primary indicator corresponding to the solution database. The customized nutrition management system according to claim 6, wherein the cause analysis unit performs an operation of the option of the same classified item to obtain a behavior characteristic value of each category. For example, the customized nutrition management system described in claim 1, wherein the nutrient intake reference data includes the reference amount of the human nutrient referenced by the Ministry of Health and Welfare, reference materials published by the American Nutritional Diet Association, and published by the World Organization. The information, the reference materials calculated based on the case data, or the reference materials obtained by mixing the case data according to the reference materials published by the above-mentioned units. The customized nutrition management system of claim 3, wherein the processing device further comprises a food conversion unit, wherein the food conversion unit converts the actual intake nutritional result of the individual into at least one a basic food type and a portion corresponding to the first basic food type, and converting the adjusted second basic food type and the portion corresponding to the second basic food type into the nutrient, wherein the nutritional formula is stored in The ingredients in the nutrition database. A method for processing a customized nutrition management system, comprising: comparing a case data with a nutritional intake reference data to generate a nutritional difference, wherein the nutritional intake reference data is a nutritional intake reference stored in the customized nutrition management system In the database; generating at least one abnormality indicator according to the corresponding relationship between the nutritional difference and the abnormality index, wherein the abnormality indicator is defined as a first main indicator, wherein the nutritional difference and the difference Corresponding relationship between the indicators is stored in a nutritional indicator database of the customized nutrition management system; and at least one first solution is generated according to the correspondence between the primary indicator and the primary indicator and the solution. The solution, wherein the correspondence between the main indicator and the solution is stored in a program database of the customized nutrition management system. The processing method of the customized nutrition management system described in claim 13 of the patent application, wherein the case data includes personal consultation reasons and problems, living diet and medication habits, personal medical history and family medical history, body position data, exercise data, Biochemical data and daily diet content. The method for processing a customized nutrition management system according to claim 14, wherein the customized nutrition management system further comprises an ingredient nutrition database, the food nutrition database comprising each item, food and/or At least one nutrient component of the health food product, wherein the treatment method further comprises: referring to the food nutrition database according to the daily diet content in the case data to calculate a person's actual nutritional intake result, and comparing the actual intake nutritional result of the individual and the nutrition The baseline data was taken to analyze the nutritional difference. For example, the processing method of the customized nutrition management system described in claim 13 further includes: selecting an option corresponding to at least one of the questions in the questionnaire data according to one of the topic relevance and correspondence between the questions The calculation formula is calculated to obtain an actual behavior value, wherein the relevance of the topic between the questions and the corresponding calculation formula are stored in a questionnaire database; comparing the actual behavior value with a behavioral benchmark data to analyze an behavior Difference, wherein the behavioral benchmark data is stored in a behavioral benchmark database and is an assessment criterion corresponding to the relevance of the topic in the questionnaire database; the difference in behavior corresponds to a behavioral difference and the heterogeneous index Corresponding relationship to generate at least one dissimilarity indicator, wherein the disparity indicator is defined as a second main indicator; and generating at least one second according to the correspondence between the main indicator and the solution according to the second main indicator solution. The processing method of the customized nutrition management system described in claim 16 further includes performing a cross-analysis or a cross-analysis of the first main index and the second main index, thereby generating at least one The ultimate main indicator. The processing method of the customized nutrition management system described in claim 17, wherein the customized nutrition management system further comprises a large data database, wherein the big data database stores at least one historical indicator. The ordering basis provided by the frequency of occurrence of the historical indicator is a weighting parameter, wherein the processing method further comprises: performing a sorting operation on the final main index according to the weighting parameter in the big data database to generate a sorting property The main indicator; and a third solution is obtained according to the main index of the ranking corresponding to the program database. The processing method of the customized nutrition management system described in claim 15 further includes converting the actual intake nutritional result of the individual into at least one first basic food type and corresponding to the first basic food according to a nutritional calculation formula. a portion of the quantity; and converting the adjusted second basic food type and the portion corresponding to the second basic food type into the nutrient, wherein the nutritional calculation formula is stored in the food nutrition database. An application for a customized nutrition management system is executed in a computer system to perform the steps described in claim 13 of the scope of the patent application. A storage medium storing a customized nutrition management system instruction set for execution in a computer system as described in claim 13 of the scope of the patent application.