CN111584037A - Nutritional data analysis guidance method for chronic diseases - Google Patents
Nutritional data analysis guidance method for chronic diseases Download PDFInfo
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- CN111584037A CN111584037A CN202010317208.1A CN202010317208A CN111584037A CN 111584037 A CN111584037 A CN 111584037A CN 202010317208 A CN202010317208 A CN 202010317208A CN 111584037 A CN111584037 A CN 111584037A
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- 235000016709 nutrition Nutrition 0.000 title claims abstract description 54
- 238000000034 method Methods 0.000 title claims abstract description 25
- 208000017667 Chronic Disease Diseases 0.000 title claims abstract description 20
- 238000007405 data analysis Methods 0.000 title claims abstract description 13
- 235000005911 diet Nutrition 0.000 claims abstract description 43
- 230000037213 diet Effects 0.000 claims abstract description 40
- 230000035764 nutrition Effects 0.000 claims abstract description 37
- 235000013305 food Nutrition 0.000 claims abstract description 18
- 230000035935 pregnancy Effects 0.000 claims abstract description 16
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 201000010099 disease Diseases 0.000 claims abstract description 9
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 9
- 239000000203 mixture Substances 0.000 claims abstract description 8
- 230000003203 everyday effect Effects 0.000 claims abstract description 4
- 235000006286 nutrient intake Nutrition 0.000 claims description 8
- 239000000463 material Substances 0.000 claims description 5
- 201000005569 Gout Diseases 0.000 claims description 3
- 206010020772 Hypertension Diseases 0.000 claims description 3
- 150000001413 amino acids Chemical class 0.000 claims description 3
- 208000007502 anemia Diseases 0.000 claims description 3
- 235000014113 dietary fatty acids Nutrition 0.000 claims description 3
- 229930195729 fatty acid Natural products 0.000 claims description 3
- 239000000194 fatty acid Substances 0.000 claims description 3
- 150000004665 fatty acids Chemical class 0.000 claims description 3
- 235000001497 healthy food Nutrition 0.000 claims description 3
- 208000004930 Fatty Liver Diseases 0.000 claims description 2
- 208000007882 Gastritis Diseases 0.000 claims description 2
- 206010019708 Hepatic steatosis Diseases 0.000 claims description 2
- 201000001431 Hyperuricemia Diseases 0.000 claims description 2
- 208000008469 Peptic Ulcer Diseases 0.000 claims description 2
- 208000019425 cirrhosis of liver Diseases 0.000 claims description 2
- 206010012601 diabetes mellitus Diseases 0.000 claims description 2
- 208000010706 fatty liver disease Diseases 0.000 claims description 2
- 235000004280 healthy diet Nutrition 0.000 claims description 2
- 230000006651 lactation Effects 0.000 claims description 2
- 208000011906 peptic ulcer disease Diseases 0.000 claims description 2
- 230000037081 physical activity Effects 0.000 claims description 2
- 238000004080 punching Methods 0.000 claims description 2
- 231100000240 steatosis hepatitis Toxicity 0.000 claims description 2
- 201000008827 tuberculosis Diseases 0.000 claims description 2
- 235000001014 amino acid Nutrition 0.000 claims 1
- 238000013500 data storage Methods 0.000 claims 1
- 235000012041 food component Nutrition 0.000 claims 1
- 230000000378 dietary effect Effects 0.000 abstract description 3
- 238000013473 artificial intelligence Methods 0.000 description 4
- 230000036541 health Effects 0.000 description 4
- 235000020931 dietary conditions Nutrition 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 208000002720 Malnutrition Diseases 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 230000036772 blood pressure Effects 0.000 description 1
- 235000019007 dietary guidelines Nutrition 0.000 description 1
- 235000020785 dietary preference Nutrition 0.000 description 1
- 235000012762 dietary quality Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 235000013666 improved nutrition Nutrition 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 235000021142 long-term diet Nutrition 0.000 description 1
- 230000001071 malnutrition Effects 0.000 description 1
- 235000000824 malnutrition Nutrition 0.000 description 1
- 235000012054 meals Nutrition 0.000 description 1
- 235000015097 nutrients Nutrition 0.000 description 1
- 208000015380 nutritional deficiency disease Diseases 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Nutrition Science (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a nutrition data analysis guidance method for chronic diseases, which comprises the following steps: a user logs in an APP; step 2: the user records personal basic information, disease information and pregnancy state of the user by using the APP; and step 3: recording the diet content of a user by using the APP every day, and establishing a food material-nutrient composition database; and 4, step 4: sending the recorded data to a data processing platform; and 5: using the dietary recording function provided by the APP if the user requires further nutritional advice; step 6: and a healthier diet analysis guidance sharing result is realized. According to the invention, the data is processed, displayed and recorded by using a proper technology in combination with the personal basic information, disease information, pregnancy state, diet content and other data of the user, then the user can share the recorded data to a doctor, and the doctor sets a new data index for the user to refer to after receiving the data, so as to help the user to eat healthier diet.
Description
Technical Field
The invention relates to various fields of accurate nutrition, an internet technology, big data, artificial intelligence, a health management technology and the like, in particular to a nutrition data analysis guidance mode aiming at chronic diseases.
Background
With the rapid development of society and the continuous improvement of economic level, the nutritional health condition of people is obviously improved, the dietary quality and the physical quality are obviously improved, and malnutrition, anemia and the like show the trend of descending year by year. But lifestyle changes also bring about nutritional problems, such as a healthy lifestyle has not yet been fully popularized, dietary structure is still not particularly rational, and chronic diseases such as hypertension, gout, etc. are also posing an increasingly serious threat to health. Balanced nutrient intake is of great importance to maintain the health of individuals and the harmonious development of society, and countries have also issued a series of documents, such as the dietary guidelines of chinese residents issued in 2016, to guide and intervene on the dietary structure and content of people. These documents improve the dietary conditions of the residents to some extent, but setting up nutritional data according to the actual conditions of each individual is troublesome, and therefore, there is no particularly significant effect.
The traditional nutrition data analysis and guidance mode aiming at chronic diseases is that doctors go to wards after meals to inquire food eaten by patients and the amount of the food eaten one by one, then blood pressure and blood sugar are measured, and the patients are told to eat more food materials and less food materials. However, this method is firstly only for patients in hospitals, and no nutrition data analysis guidance is performed on patients at home, and secondly, doctors do not set specific amount for patients in the guidance process, and since each person has different concepts of more and less, it is difficult to analyze and guide patients without accurate nutrition data indexes.
Disclosure of Invention
Based on the current situation, the invention provides a nutrition data analysis guidance method for chronic diseases, which records the diet data of a user and sends the diet data to a doctor by means of an internet technology and an artificial intelligence algorithm, and then the doctor sets standard nutrition data for guidance analysis after receiving the data.
The invention relates to a nutrition data analysis guidance method aiming at chronic diseases, which comprises the following steps:
1. a nutrition data analysis guidance method for chronic diseases is characterized by comprising the following steps:
step 1: a user logs in an APP;
step 2: the user records personal basic information, disease information and pregnancy state of the user by using the APP, and the APP is used for dynamically adjusting and generating a nutrition intake suggestion standard aiming at the physical state of the user;
and step 3: recording the diet content of a user everyday by using the APP, establishing a food material-nutrient composition database, and converting the data through the food material-nutrient composition database to obtain the actual nutrient intake of the user;
and 4, step 4: sending the recorded data to a data processing platform, and generating nutrition intake conditions for the user after processing, wherein the nutrition intake conditions comprise intake suggestion standards and actual nutrition intake;
this is then shown by means of radar maps and the APP can also record 3 days or long term diet data.
And 5: if the user needs further nutrition suggestion, the diet record function provided by the APP is used, the user selects to check the diet record of the user for three days or the diet record for a long time, and after the user finishes checking, the diet record is shared to the doctor;
step 6: after the doctor received the diet record, set for the data index according to user's actual conditions, set for different nutrition data indexes, after the doctor set for the nutrition data index, new index can show in user's healthy food APP to help the user to contrast own each item data, discover the problem of oneself, thereby realize more healthy diet analysis and guide and share the result.
Compared with the prior art, the method and the system can combine personal basic information, disease information, pregnancy state and diet information of the user, analyze the data by using an internet technology and an artificial intelligence algorithm, share the data to a doctor, and set the nutrition index after the doctor receives the data, so as to help the user to eat healthier diet.
Drawings
FIG. 1 is a schematic overall flow chart of a method for analyzing and guiding nutritional data for chronic diseases according to the present invention;
fig. 2 is a login interface diagram of a smartphone APP according to an embodiment of the present invention;
fig. 3 is a diagram of a diet card interface of a smartphone APP according to an embodiment of the present invention; (a) a diet file; (b) displaying by a doctor; (c) and displaying by the user.
Detailed Description
Embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
Fig. 1 shows an overall flowchart of a method for analyzing and guiding nutritional data for chronic diseases according to the present invention. The method comprises the following steps of firstly, comprehensively processing and analyzing data such as personal basic information, disease information and diet information of a user, then transmitting the data to a doctor, finally, receiving the data by the doctor, setting a new nutrition data index, and carrying out nutrition data analysis guidance on the user according to the new nutrition data index to help guide the user to eat healthier diet, wherein the method specifically comprises the following steps:
step 1, a user logs in a smart phone APP provided by the invention, and can log in through any one of two modes, namely a mobile phone number and a WeChat mode, wherein the smart phone APP has the functions of medical service, diet card punching and the like;
step 2, recording personal basic information, disease information and pregnancy state of a user by using the APP, wherein the personal basic information comprises contents such as gender, height, weight, age, dietary preference, nationality, food taboo, physical activity intensity and the region where the user is located; the disease information comprises whether gastritis, fatty liver, diabetes, hypertension, peptic ulcer, liver cirrhosis, hyperuricemia, gout, tuberculosis, anemia and the like exist; the pregnancy state comprises non-pregnancy, early pregnancy, middle pregnancy, late pregnancy, lactation and the like; these data are used to dynamically adjust and generate nutrient intake recommendation criteria for the user's physical state;
step 4, the recorded data are sent to a data processing platform, nutrition intake conditions (including intake suggestion standards and actual nutrition intake) for the user are generated after processing, and are displayed in the APP in a radar map form, so that the user can clearly and visually observe the own nutrition intake conditions, and the user can be certain to grasp and know the own nutrition intake; meanwhile, the APP is used for recording diet data for three days or a long time, and a user can check the diet data for three days or a long time through the APP;
the user re-recording new data is done by repeating steps 3, 4, 5, 6.
In the aspect of data analysis and processing, the method establishes cooperation with hospitals to acquire early-stage research data, can ensure the authenticity and reliability of the research data, simultaneously provides a proper implementation way for the method by an artificial intelligence technology and an internet technology, establishes contact with users in the aspect of data sharing, and allows the users to share and record own dietary conditions and share the dietary conditions to doctors. The above points make it possible to realize a nutrition data analysis guidance mode aiming at chronic diseases.
The present invention is not limited to the above-described process, and any combination of the features or novel steps disclosed in the present invention can be extended to fall within the scope of the present invention.
Claims (9)
1. A nutrition data analysis guidance method for chronic diseases is characterized by comprising the following steps:
step 1: a user logs in an APP;
step 2: the user records personal basic information, disease information and pregnancy state of the user by using the APP, and the APP is used for dynamically adjusting and generating a nutrition intake suggestion standard aiming at the physical state of the user;
and step 3: recording the diet content of a user everyday by using the APP, establishing a food material-nutrient composition database, and converting the data through the food material-nutrient composition database to obtain the actual nutrient intake of the user;
and 4, step 4: sending the recorded data to a data processing platform, and generating nutrition intake conditions for the user after processing, wherein the nutrition intake conditions comprise intake suggestion standards and actual nutrition intake;
and 5: if the user needs further nutrition suggestion, the diet record function provided by the APP is used, the user selects to check the diet record of the user for three days or the diet record for a long time, and after the user finishes checking, the diet record is shared to the doctor;
step 6: after the doctor received the diet record, set for the data index according to user's actual conditions, set for different nutrition data indexes, after the doctor set for the nutrition data index, new index can show in user's healthy food APP to help the user to contrast own each item data, discover the problem of oneself, thereby realize more healthy diet analysis and guide and share the result.
2. The method for analyzing and guiding nutrition data aiming at chronic diseases as claimed in claim 1, wherein the smart phone APP in step 1 includes functions of medical service, diet card punching and the like, and the user logs in through any one of two modes of mobile phone number and WeChat.
3. The method for analyzing and guiding nutritional data according to claim 1, wherein the basic information of the person obtained in step 2 at least comprises sex, height, weight, age, diet preference, ethnicity, food contraindication, physical activity intensity, location, etc.; the disease information comprises whether gastritis, fatty liver, diabetes, hypertension, peptic ulcer, liver cirrhosis, hyperuricemia, gout, tuberculosis, anemia and the like exist; the pregnancy status includes non-pregnancy, early pregnancy, middle pregnancy, late pregnancy, and lactation.
4. The method for guiding analysis of nutritional data for chronic diseases according to claim 1, wherein the food material-nutritional component database in step 3 contains information on basic nutritional components, amino acids and fatty acids corresponding to at least 4000 food materials and dishes.
5. The method for analyzing and guiding nutritional data for chronic diseases as claimed in claim 1, wherein the data processing platform in step 4 comprises a data receiving module, a data processing and analyzing module, a data storage module and a data output module, and is responsible for analyzing and storing all data of the user.
6. The method for guiding analysis of nutritional data for chronic diseases according to claim 1, wherein the recommended standard for nutrient intake and the actual nutrient intake obtained in step 4 are displayed in the form of radar chart for the user to clearly and intuitively observe his/her nutrient intake status.
7. The method for analyzing and guiding nutrition data for chronic diseases according to claim 1, wherein a function of viewing the record of the user's diet card for three days or for a long period of time is provided in step 4 to prevent forgetting the user's diet data.
8. The method for analysis guidance of nutritional data for chronic diseases according to claim 1, wherein a function of setting data index by a user after a doctor receives a record is provided in step 6, thereby obtaining a result of implementing healthier diet analysis guidance.
9. The method for guidance in analysis of nutritional data for chronic diseases according to claim 1, wherein the user re-recording new data is done by repeating steps 3, 4, 5, 6.
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| CN202010317208.1A CN111584037A (en) | 2020-04-21 | 2020-04-21 | Nutritional data analysis guidance method for chronic diseases |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116779104A (en) * | 2023-05-06 | 2023-09-19 | 广州昆华医疗科技有限公司 | Intelligent medical response method based on big data and intelligent medical cloud computing system |
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| CN108182969A (en) * | 2017-12-12 | 2018-06-19 | 昆明亿尚科技有限公司 | A kind of online interrogation system of nutritionist and method |
| CN109273070A (en) * | 2018-09-06 | 2019-01-25 | 北京好价网络科技有限公司 | Dietetic nutrition analysis system and method |
| CN109448813A (en) * | 2018-09-08 | 2019-03-08 | 天津大学 | A method of dietary data is recorded and analyzes by stage to remind movement |
| CN110797108A (en) * | 2019-10-30 | 2020-02-14 | 武汉绿安健膳方科技有限公司 | Targeted household diet nutrition intervention method and management system |
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Patent Citations (5)
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| CN107680652A (en) * | 2017-09-13 | 2018-02-09 | 天津大学 | A kind of nutrition dietary based on machine learning recommends and evaluation method |
| CN108182969A (en) * | 2017-12-12 | 2018-06-19 | 昆明亿尚科技有限公司 | A kind of online interrogation system of nutritionist and method |
| CN109273070A (en) * | 2018-09-06 | 2019-01-25 | 北京好价网络科技有限公司 | Dietetic nutrition analysis system and method |
| CN109448813A (en) * | 2018-09-08 | 2019-03-08 | 天津大学 | A method of dietary data is recorded and analyzes by stage to remind movement |
| CN110797108A (en) * | 2019-10-30 | 2020-02-14 | 武汉绿安健膳方科技有限公司 | Targeted household diet nutrition intervention method and management system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116779104A (en) * | 2023-05-06 | 2023-09-19 | 广州昆华医疗科技有限公司 | Intelligent medical response method based on big data and intelligent medical cloud computing system |
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Application publication date: 20200825 |