CN114913958A - Diet nutrition dynamic intervention system and method based on user portrait technology - Google Patents
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- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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Abstract
The invention discloses a dynamic intervention system and method for dietary nutrition based on a user portrait technology, which comprises the steps of constructing a user portrait model by collecting a user evaluation questionnaire and previous medical information, and obtaining a user label through the user portrait model; obtaining a target energy demand according to the user basic information, the activity information and the medical information in the user label; basic information and medical information to obtain nutrient requirements; obtaining drinking water requirements according to the basic information; obtaining corresponding energy and nutrients according to the type and weight of food; generating a recipe according to the diet guidance, firstly filtering the food through the medical information of the user, and then matching the energy, the nutrients and the weight of the filtered food with the diet guidance to generate the recipe; monitoring the change of user information, updating user labels, and dynamically adjusting diet guidance and recipes.
Description
Technical Field
The invention relates to the fields of computers, medical health and technology, in particular to a diet nutrition dynamic intervention system and method based on a user portrait technology.
Background
In recent years, with the change of national economic and social life styles, the living standard of people is obviously improved, the living style is also obviously changed, the number of overweight/obese people is in a rapid rising trend, and in practice, necessary nutritional intervention is needed in order to improve the living quality of chronic disease groups and reduce the medical expenses caused by diseases.
Dietary nutritional intervention is a scientific, systematic theory, with high complexity and variability in the real world population. How to apply theory to practice is a difficult problem to give a good experience to the user population. On one hand, the individual needs of wide patients are difficult to meet due to the extreme shortage of professional dieticians; on the other hand, the existing nutrition intervention modes are mostly evaluated face to face and intervention suggestions are provided, so that the efficiency is low, and the nutrition intervention effect of patients is difficult to be monitored and monitored continuously.
Conventionally, the efficiency problem can be solved through the convenience of the mobile device, the physical information, the physiological index information, the illness state information and the like of the patient are acquired and known, then the dietician analyzes the information according to professional knowledge and experience or the system classifies the information by using some basic rules, and an intervention scheme of the type and the amount information of the ingestible food is provided for the patient. During execution, self-monitoring of dietary intake and physical activity is achieved, and mobile applications increase the potential for extending the coverage and effectiveness of dietary nutritional interventions, thereby helping users to better improve quality of life. The prior art has the following disadvantages:
(1) the intelligent degree is low, only the problem of efficiency of information acquisition is solved, and a nutriologist is still required to analyze according to individual conditions.
(2) The accuracy of the nutritional intervention scheme is not stable and depends heavily on the professional experience and judgment of the dietician.
(3) The condition of an individual is constantly changing and nutritional intervention should not be constant. Dynamic nutritional intervention programs can lead to better results.
(4) Poor compliance with intervention programs, mainly in the content provided by the programs (such as recipes), results in poor performability due to poor quality.
Disclosure of Invention
In order to solve the defects of the prior art, a personalized nutrition intervention scheme is recommended for a user, the accuracy of the nutrition intervention scheme is improved, and the compliance of the user is improved, the following technical scheme is adopted in the invention:
a dynamic intervention method for meal nutrition based on a user portrait technology comprises the following steps:
step S1: collecting a user evaluation questionnaire and past medical information;
the assessment questionnaire comprises basic information and life habit information of the user, wherein the basic information comprises the sex, the height and the weight of the user; the living habit information comprises the dietary preference, dietary contraindication and current activity intensity of the user;
the existing medical information comprises a user's medical record, a hospitalization record, a prescription record, an examination report record and an inspection report record;
step S2: according to the collected data, a user portrait model is built, a user label is obtained through the user portrait model, and the user label comprises: user basic information, activity information, medical information;
step S3: obtaining a user diet guide through the constructed nutrition scheme model according to the user label, wherein the user diet guide comprises the following steps: target energy demand, nutrient demand, water demand and food weight, the acquisition of dietary guidelines comprising the steps of:
step S3.1: obtaining a target energy demand according to the basic information, the activity information and the medical information of the user;
step S3.2: obtaining nutrient requirements according to the basic information and the medical information;
step S3.3: obtaining drinking water requirements according to the basic information;
step S3.4: obtaining corresponding energy and nutrients according to the type and weight of food;
step S4: generating a recipe according to the diet guidance, filtering food through user medical information, and matching energy, nutrients and weight of the filtered food with the diet guidance to generate the recipe;
step S5: monitoring the change of user information, updating user labels, and dynamically adjusting diet guidance and recipes.
Further, the calculation of the target energy requirement in step S3.1 includes the following steps:
step S3.1.1: calculating an energy demand EER = BMR IF AF; wherein BMR represents the basic metabolic energy, and the corresponding basic metabolic energy is obtained through the basic information in the user label; the IF represents a disease factor, the disease information of the user is obtained through the medical information in the user label, and the disease factor is set according to the degree of the disease and the treatment condition; AF represents an activity factor, the activity intensity of the user is obtained through activity information in the user label, and the activity factor is set according to the activity intensity of the user;
step S3.1.2: and calculating a target energy demand, and setting the energy demand corresponding to the user through the basic information of the user in the user label.
Further, the basic information in step S2 includes the weight, height, waist size, and sex of the user, and in step S3.1.2, the height-weight coefficient BMI = weight/height is set, and the target energy requirement corresponding to the user is set according to the value ranges of the set height-weight coefficient, sex, and waist size.
Further, the basic information in the step S2 includes the age, weight, and sex of the user; the energy requirement in the step S3.1.1 is a daily energy requirement, and is divided according to age and gender, and calculated according to weight and energy coefficient to obtain corresponding basal metabolic energy at different ages and different genders.
Further, the medical information in step S2 includes the disease type, the degree of illness and the treatment information of the user, and the disease factor in step S3.1.1 is set according to the disease type, the degree of illness and the treatment information.
Further, the basic information in the step S2 includes age, and the activity information includes current activity intensity; the activity factor in step S3.1.1 is set according to the age of the user and the current activity intensity.
Further, the basic information in step S2 includes the user' S weight, the medical information includes disease information and medical treatment status, and the activity information includes the current status of the user; the calculation of nutrient requirements in step S3.2 comprises the steps of:
step S3.2.1: calculating the protein demand, and obtaining the protein demand according to the cause, type and degree of diseases, the current state and treatment condition of the user through the weight and the disease information of the user; converting the functional protein amount based on the protein requirement;
step S3.2.2: calculating the functional carbohydrate amount according to the energy requirement, and converting the functional carbohydrate amount into the carbohydrate requirement;
step S3.2.3: the amount of the functional fat is calculated from the energy requirement, the amount of the functional protein and the amount of the functional carbohydrate, and the daily amount of the fat requirement is converted from the amount of the functional fat.
Further, the basic information in step S2 includes the weight of the user, and in step S3.3, the required drinking amount is calculated according to the weight of the user.
Further, the food category and weight in step S3.4 are to classify the food into 11 categories, and set the food weights of 6 categories of vegetables, fruits, milk, eggs, hard fruits and fats and the corresponding carbohydrates, proteins, fats and energies; setting the weight ranges of 5 types of cereals X, potatoes Y, soybeans Z, red meat M and aquatic seafood N, and calculating corresponding carbohydrate, protein, fat and energy according to the weight ranges and the proportioning coefficient.
A dynamic intervention system for meal nutrition based on user profiling technology, on which a computer program is stored which, when executed by a processor, implements a method for dynamic intervention for meal nutrition based on user profiling technology.
The invention has the advantages and beneficial effects that:
according to the method, the user portrait is constructed by acquiring the user data, the diet guide is generated by utilizing the user portrait, the recommended recipe is obtained through the diet guide, the intelligent degree is improved, the accuracy and the stability of the nutritional intervention scheme are improved, the transitional dependence on a dietician is avoided, the nutritional intervention scheme is dynamically updated along with the user through updating the user portrait, the compliance of the intervention scheme is improved, the quality of the recommended recipe is improved, and the execution performance is improved.
Drawings
FIG. 1 is a flow chart of a method of an embodiment of the present invention.
Fig. 2 is a schematic system structure according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
As shown in fig. 1, the system and method for dynamic intervention of dietary nutrition based on user profile technology includes the following steps:
step S1: patient assessment questionnaires and past medical information are collected.
The evaluation questionnaire is filled in and obtained by the user and is used for collecting the basic information and the living habit information of the user. The basic information comprises the sex, the height, the weight and the like of the user; the life habit information comprises dietary preference, dietary contraindication, current working strength and the like.
The past medical information is filled in by a user or acquired by a medical institution data interface and is used for acquiring the medical record, the hospitalization record, the prescription record, the examination report record, the inspection report record and the like of the user.
In the embodiment of the invention, multi-dimensional information (basic information, past medical information, life habit information and the like) of a user is collected from each channel, and a health file is summarized and created; the specific collected information includes: age, height, weight, type of daily activity, religious belief, diagnosis, surgical information, pharmaceutical information; the specific collection channel comprises: the small program evaluates questionnaires and management end special disease files for the first time; simulating Zhang III of users, wherein the information acquisition comprises the following steps:
basic information: sex: male; age: age 32 years old; height: 175 cm; weight: 80 kg;
the type of daily activity: drying and surviving in the construction site; religious beliefs: buddhism;
disease information: and (3) diagnosis: thyroid cancer; operation information: thyroidectomy; the drugs are being taken: youmeile.
Step S2: for the collected data, a user tag is generated using the user profile model.
In the embodiment of the invention, user information is analyzed, and a user label simulating Zhang III of a patient is constructed by using a well-trained portrait model: [ 17-50 years of age ] for men [ surgery ] for meat and fishy [ 80kg ] for BMI: 24-28, biguanide drugs, and the like.
Step S3: and calculating the diet guidance of the user through a nutrition scheme construction model according to the user label, wherein the diet guidance comprises target EER (energy demand for meal), three nutrient energies and weights, water intake and eleven major food weights. Nouns/terms are shown in table 1:
table 1: noun/glossary
Calculating the dietary guidelines comprises the steps of:
step S3.1: guidance of a target daily energy demand comprising the steps of:
step S3.1.1: calculating daily energy demand EER: EER = BMR IF AF
The formula for calculating the BMR is shown in Table 2, and the age, weight and sex are all from the user labels.
Table 2: basic metabolism energy calculating table
Values of disease factor IF: the disease information is from the user tag, as shown in table 3.
Table 3: disease factor calculation table
Activity factor AF value: gender, current activity intensity, are from user tags as shown in table 4.
Table 4: activity factor calculation table
Step S3.1.2: calculate target daily energy requirement EER, set BMI = weight/height, weight, height, waist circumference, gender data from user tags as shown in table 5.
Table 5: target daily energy demand calculation table
Step S3.2: the method for guiding the three nutrients comprises the following steps:
step S3.2.1: protein EP & P, daily protein requirement P (g/kg body weight), was calculated as shown in Table 6.
Table 6: daily protein requirement calculation Table
The functional protein amount per day ep (kcal) = P4 (4 is a fixed conversion factor).
Step S3.2.2: calculating carbohydrate ECHO & CHO;
functional amount of carbohydrates echo (kcal) = EER 0.5 per day (0.5 is a fixed conversion factor);
daily carbohydrate demand CHO (g/kcal) = ECHO/4 (4 is a fixed conversion factor);
step S3.2.3: calculating fat EF & F;
daily functional fat mass ef (kcal) = EER-EP-ECHO;
daily fat demand F (g/kcal) = EF/9 (9 is a fixed conversion coefficient);
step S3.3: guidance of water intake Fluid;
fluid = body weight 30 (30 is a fixed scaling factor);
step S3.4: calculate 11 major food weights, where 6 major groups below are fixed as shown in table 7;
table 7: fixed weight of 6 kinds of food
The remaining 5 major classes were calculated by the formula shown in table 8;
table 8: fixed weight of 5 major food
In the embodiment of the invention, according to the user label and other information, a model is constructed through a nutrition scheme, and personalized diet guidance is output
Simulating Zhang III of a patient, calculating EER, target EER, three nutrients, water and 11 kinds of food weight according to a user portrait, wherein the calculation method comprises the following steps:
（1）EER = BMR * IF * AF=【（ 15.3 * 80 + 679）* 0.95】*【1】*【1.55】=2802kacl
(2) target EER = EER-400=2402kcal
(3) Three nutrients and water:
protein: EP (kcal) = P4 (80-120 g, 320-480 kcal)
Carbohydrate: ECHO (kcal) = EER (0.5-0.65); CHO (g/kcal) = ECHO/4
Fat: ef (kcal) = EER-EP-ECHO; f (g/kcal) = EF/9
Water intake: body weight (30-35)
The diet generation guidelines were as follows:
three nutrients and water: protein (80-120 g, 320-480 kcal), carbohydrate (155-202 g, 1400-1820 kcal), fat (46-120 g, 420-1080 kcal), and water intake (2400-2800 ml);
11 weight of the main food:
500 g of vegetables (common), 300 g of fruits (common), 240g of milk (common), 50g of eggs (common), 9 g of nuts (common), 25 g of grease (common), 40g of grains (common), 10 g of potatoes (common), 20g of soybeans (common), 30 g of red meat (common), and 20g of aquatic seafood (common).
Step S4: daily recipes were generated according to the dietary guidelines generated in step 3. In the generation process, improper dishes in the dish library are filtered according to the taboo labels in the user labels, and then the rest dishes are matched, so that the energy and weight of three nutrients and the weight of eleven major foods in a plurality of dishes just meet diet guidance, and the up-and-down fluctuation of each index is not more than 10%.
The weight ratio of the food for each meal is shown in table 9;
table 9: daily dietary structure recommendation
| Number of meals | Food type and recommended amount |
| Breakfast | 50g egg, 100 g vegetable and X/8 g cereal |
| Breakfast food | Y g potatoes, 240g of milk and 100 g of fruit |
| Lunch | 200g of vegetables, 12 g of oil, Z/2 g of soybean, X3/8 g of cereals, M g of livestock and poultry meat |
| Lunch | 9 g nut and 100 g fruit |
| Dinner | 200g of vegetables, 12 g of oil, Z/2 g of soybeans, X3/8 g of cereals and N g of aquatic products |
| Evening meal | 100 g fruit + X/8 g cereal |
The specific dish mode is calculated as follows:
taking breakfast as an example, three dishes are needed, which are A, B, C respectively, and AW, BW and CW respectively, the weight of each dish is unit gram, then the dishes need to meet the following conditions:
AW a/g + BW B/g + CW C/g = 50
AW A/g + BW B/g + CW/g + C/g = 100
AW X a trough weight/g + BW X B trough weight/g + CW C trough weight/g = X/8
Finally, outputting three dishes A, B, C meeting the conditions, wherein the weights of the dishes are AW, BW and CW, and forming a menu.
In the embodiment of the invention, according to diet guidance, a daily diet is generated through a diet recommendation algorithm and is delivered to a patient through a small program; according to the EER, the target EER, the three nutrients, the water and the weight of the 11 types of food calculated in the step 3, and in combination with a food material knowledge base, the model automatically generates a recommended recipe as follows:
breakfast (583 kcal): 200g of assorted noodles, 200g of deluxe and 50g of boiled eggs
Chinese meal (901 kcal): 160g of minced meat green vegetables, 276g of spinach ball soup and 120g of black rice and brown rice
Lunch plus (183 kcal): 250g of plum and apricot and 15g of nut
Dinner (736 kcal): 120g of black rice and brown rice, 200g of steamed grouper and 240g of tomato and bean curd soup
Step S5: monitoring the change of user information, updating user labels, and dynamically adjusting diet guidance and recipes.
Corresponding to the embodiment of the diet nutrition dynamic intervention method based on the user portrait technology, the invention also provides an embodiment of a diet nutrition dynamic intervention system based on the user portrait technology.
Referring to fig. 2, the diet nutrition dynamic intervention system based on the user profile technology provided by the embodiment of the invention includes a memory and one or more processors, wherein the memory stores executable codes, and the one or more processors execute the executable codes to implement the diet nutrition dynamic intervention method based on the user profile technology in the above embodiment.
The embodiment of the dynamic meal nutrition intervention system based on the user profiling technology can be applied to any equipment with data processing capability, such as computers and other equipment or devices. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. The software implementation is taken as an example, and as a logical device, the device is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory for running through the processor of any device with data processing capability. From a hardware aspect, as shown in fig. 2, a hardware structure diagram of any device with data processing capability in which the dynamic meal nutrition intervention system based on the user profile technology of the present invention is located is shown, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 2, any device with data processing capability in the embodiment may also include other hardware generally according to the actual function of the any device with data processing capability, which is not described again.
The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the invention. One of ordinary skill in the art can understand and implement it without inventive effort.
The embodiment of the invention also provides a computer readable storage medium, which stores a program, and when the program is executed by a processor, the program realizes the dynamic intervention method of meal nutrition based on the user portrait technology in the above embodiment.
The computer readable storage medium may be an internal storage unit, such as a hard disk or a memory, of any data processing device described in any previous embodiment. The computer readable storage medium may also be any external storage device of a device with data processing capabilities, such as a plug-in hard disk, a Smart Media Card (SMC), an SD Card, a Flash memory Card (Flash Card), etc. provided on the device. Further, the computer readable storage medium may include both an internal storage unit and an external storage device of any data processing capable device. The computer-readable storage medium is used for storing the computer program and other programs and data required by the arbitrary data processing-capable device, and may also be used for temporarily storing data that has been output or is to be output.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and these modifications or substitutions do not depart from the scope of the embodiments of the present invention in nature.
Claims (10)
1. A dynamic intervention method for meal nutrition based on a user portrait technology is characterized by comprising the following steps:
step S1: collecting a user evaluation questionnaire and past medical information;
step S2: according to the collected data, a user portrait model is built, a user label is obtained through the user portrait model, and the user label comprises: user basic information, activity information, medical information;
step S3: obtaining a user diet guide through the constructed nutrition scheme model according to the user label, wherein the user diet guide comprises the following steps: target energy demand, nutrient demand, water demand and food weight, the acquisition of dietary guidelines comprising the steps of:
step S3.1: obtaining a target energy demand according to the basic information, the activity information and the medical information of the user;
step S3.2: obtaining nutrient requirements according to the basic information and the medical information;
step S3.3: obtaining drinking water requirements according to the basic information;
step S3.4: obtaining corresponding energy and nutrients according to the type and weight of food;
step S4: generating a recipe according to the diet guidance, filtering food through user medical information, and matching energy, nutrients and weight of the filtered food with the diet guidance to generate the recipe;
step S5: monitoring the change of user information, updating user labels, and dynamically adjusting diet guidance and recipes.
2. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the calculation of the target energy requirement in step S3.1 includes the following steps:
step S3.1.1: calculating an energy demand EER = BMR IF AF; wherein BMR represents the basic metabolic energy, and the corresponding basic metabolic energy is obtained through the basic information in the user label; the IF represents a disease factor, the disease information of the user is obtained through the medical information in the user label, and the disease factor is set according to the degree of the disease and the treatment condition; AF represents an activity factor, the activity intensity of the user is obtained through activity information in the user label, and the activity factor is set according to the activity intensity of the user;
step S3.1.2: and calculating a target energy demand, and setting the energy demand corresponding to the user through the basic information of the user in the user label.
3. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 2, wherein:
the basic information in step S2 includes the weight, height, waist size, and sex of the user, and in step S3.1.2, the height-weight coefficient BMI = weight/height is set, and the target energy requirement corresponding to the user is set according to the value ranges of the height-weight coefficient, the sex, and the waist size.
4. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the basic information in the step S2 includes the age, weight and sex of the user; the energy requirement in the step S3.1.1 is a daily energy requirement, and is divided according to age and gender, and calculated according to weight and energy coefficient to obtain corresponding basal metabolic energy at different ages and different genders.
5. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the medical information in step S2 includes the disease type, the degree of illness and the treatment information of the user, and the disease factor in step S3.1.1 is set according to the disease type, the degree of illness and the treatment information.
6. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the basic information in the step S2 includes age, and the activity information includes current activity intensity; the activity factor in step S3.1.1 is set according to the age of the user and the current activity intensity.
7. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the basic information in the step S2 includes the user 'S weight, the medical information includes disease information and medical conditions, and the activity information includes the user' S current status; the calculation of nutrient requirement in step S3.2 comprises the steps of:
step S3.2.1: calculating the protein demand, and obtaining the protein demand according to the cause, type and degree of diseases, the current state and treatment condition of the user through the weight and the disease information of the user; converting the functional protein amount based on the protein requirement;
step S3.2.2: calculating the functional carbohydrate amount according to the energy requirement, and converting the functional carbohydrate amount into the carbohydrate requirement;
step S3.2.3: the amount of the functional fat is calculated from the energy requirement, the amount of the functional protein and the amount of the functional carbohydrate, and the daily amount of the fat requirement is converted from the amount of the functional fat.
8. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the basic information in step S2 includes the weight of the user, and in step S3.3, the required water intake is calculated according to the weight of the user.
9. A method of dynamic intervention in dietary nutrition based on user profile technology as claimed in claim 1, wherein: the food category and weight in step S3.4 are obtained by classifying the food into 11 categories, and setting the food weights of 6 categories of vegetables, fruits, milk, eggs, hard fruits and fats and the corresponding carbohydrates, proteins, fats and energies; setting the weight ranges of 5 types of cereals X, potatoes Y, soybeans Z, red meat M and aquatic seafood N, and calculating corresponding carbohydrate, protein, fat and energy according to the weight ranges and the proportioning coefficient.
10. A system for dynamic intervention in diet nutrition based on user profiling technology, characterized in that a computer program is stored thereon, which program, when executed by a processor, implements the method according to any one of claims 1 to 9.
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