CN109817307A - Nutritious food order system and its implementation based on smart machine - Google Patents
Nutritious food order system and its implementation based on smart machine Download PDFInfo
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Abstract
The present invention discloses nutritious food order system and its implementation based on smart machine, solves the problems, such as that the prior art timely and effective cannot improve nutrient health for user's recommending recipes.The present invention includes core processor, smart machine, Nutritional Risk module, dietary recommendations continued and make a reservation module, nutritionist's warning module and memory module.Implementation method, comprising the following steps: acquire the basic information and Nutritional risk screening scale of user by smart machine first；Secondly Nutritional Risk module carries out automatically analyzing calculating, and dietary recommendations continued matches recommending recipes with module of making a reservation and is presented to the user.The present invention acquires basic information and Nutritional risk screening scale by inquiry, and calculate analysis data automatically according to built-in algorithm, and assessment classification guidance is carried out automatically, it can effectively reduce time and human cost, more efficiently, the Nutritional risk screening coverage rate of user is improved, the improvement rate of patient's nutritional support is promoted, mitigate user's nutrition improvement expense, is conducive to promote in the art.
Description
Technical field
The present invention relates to nutritious food order systems and its implementation based on smart machine.
Background technique
As people's living standard improves, great variety occurs for dietary structure, nutrition condition.It is inferior health, nutritionally relevant
Disease, if Overweight-obesity, diabetes, nephrosis chronic diseases are popular year by year, have become influences the global of human health at present
Public health problem.
Currently, Nutritional Status of Patients is usually by having the clinical nutrition Shi Jinhang screening of professional skill, then assigns nutrition and control
Treatment scheme, including enteral nutrition preparation, parenteral nutrition and nutritious food.For chronic, in digestive tract function, swallow
Masticatory function is all in normal situation, is preferred from clinical nutrition Shi Jianyi and to the diet section targeted nutritious food of order
Scheme, and hospital's nutritious food is usually to be distributed to ward with hospital's dining car after being prepared by Nutriology Dept..
However, due to current China clinical nutrition teacher personnel amount wretched insufficiency, and each patient of screening and formulation nutrition
It requires to take some time when scheme, causes the Nutritional Risk of patient that cannot be found in time, can not implement to seek in time
It supports and intervenes.Secondly, China its people nutrient health knowledge is short of, nutritionist is only equipped in the professional medicals mechanism such as hospital, community etc.
The substantially nonnutritive health service of grass-roots unit, coverage rate is low, and the approach that patient obtains professional nutrient knowledge is single and difficult.
The present invention carries out network surveying with Nutritional risk screening scale by the basic information investigation based on smart machine, receives
Collect user information, calculates and assess automatically basal nutrient situation and the battalion of patient with tax subsystem further according to the algorithm built in system
Risk is supported, and provides report and nutrition Suggestion.Motion conditions and body fat rate of the present invention according to the user being collected into, automatic calculating
The energy requirement of patient, then the Nutritional Risk scoring of comprehensive patient, energy requirement, targetedly Automatic Adaptation Data library
In recommending recipes, patient can realize self-service order nutritious food within the system, can be effectively improved the nutrient health shape of user
Condition.
Nutritional Risk: refer to that trophic factor leads to the affected risk of patient clinical final result, it is emphasised that having with nutrition
The disease outcome of pass occurs.Body-mass index: Body Mass Index, abbreviation BMI.It is with weight kilogram number divided by height
The several squares of numbers obtained of rice are a standards for commonly measuring body weight and health status in the world at present.Basic generation
Thank to rate: Basal Metabolic Rate, abbreviation BMR.Refer in the unit time consumed by every square metre of body surface area of human body
Basic metabolism energy is commonly used to indicate the level of basic metabolism.
Summary of the invention
The technical problem to be solved by the present invention is providing the nutritious food order system based on smart machine and its realization side
Method solves the problems, such as that the prior art timely and effective cannot improve nutrient health for user's recommending recipes.
To achieve the above object, The technical solution adopted by the invention is as follows:
Nutritious food order system based on smart machine, including core processor pass through network with the core processor
The smart machine of connection, and the Nutritional Risk module, dietary recommendations continued and the module of making a reservation that are connect respectively with the core processor；
The dietary recommendations continued and module of making a reservation are stored with recommending recipes, and mode of the smart machine for by inquiry acquires user's base
Basic information collected is simultaneously passed through transmission of network to the core processor by plinth information, and the core processor is used for institute
The basic information received handle and information is sent to the Nutritional Risk module, the Nutritional Risk mould by treated
Block will automatically analyze calculating result and feed back to the core processing for carrying out automatically analyzing calculating to received information
Automatically analyzing of receiving is calculated result and is respectively sent to the smart machine and the diet pushes away by device, the core processor
It recommends and makes a reservation module, the dietary recommendations continued automatically analyzes the recommendation for calculating result and storing in it with what module of making a reservation will receive
Recipe carries out Auto-matching and matching result is sent to the smart machine, the core processing by the core processor
Device is connected with nutritionist's warning module and for storing data memory module of information.
Further, the smart machine is equipped with input module and display module, and the input module is for realizing user
With the human-computer interaction between the smart machine, the display module be used for automatically analyze calculate result, matching result and
The display of survey item when investigating basic information.
Further, the smart machine is smart phone, tablet computer, desktop computer or laptop.
The implementation method of nutritious food order system based on smart machine, comprising the following steps:
Step S1, the basic information and Nutritional risk screening scale of user are acquired in such a way that smart machine is using investigation
And basic information collected and Nutritional risk screening scale are passed through into transmission of network to core processor；
Step S2, core processor handles the basic information received and Nutritional risk screening scale, and will place
Reason result is sent to memory module and is stored, while being also communicated to Nutritional Risk module and carrying out automatically analyzing calculating, and automatic point
Analysis calculated result feeds back to core processor, this is automatically analyzed calculating result again and is respectively sent to smart machine by core processor
With dietary recommendations continued and module of making a reservation, user determines whether to order nutrition according to the calculating result that automatically analyzes that smart machine receives
Meal, if ordering, dietary recommendations continued with make a reservation module by automatically analyzing of receiving calculate the recommending recipes that are stored with it of result into
Matching result is simultaneously sent to smart machine by core processor and is presented to the user by row Auto-matching.
Specifically, in the step S1, the investigation content of the basic information includes the height of user, gender, goes out
Phase birthday, weight and body fat percentage information.
Specifically, in the step S1, the investigation content of the Nutritional risk screening scale includes the disease of user
Situation, weight loss situation, food-intake decline situation and exercise intensity and the information of time.
Specifically, Nutritional Risk module automatically analyze calculating and dietary recommendations continued and order in the step S2
When module of eating matching recommending recipes, comprising the following steps:
User's height, weight, the basal nutrient situation of body fat percentage information evaluation user that step 1, basis are collected into；
Step 2 is built according to the Nutritional risk screening scale information being collected into, progress automatic scoring and Nutritional Risk report
View；
The exercise intensity for the user that step 3, basis are collected into and time and calculated body fat percentage, it is automatic to calculate
Energy requirement.
The automatic calculated body fat percentage of step 4, basis, Nutritional Risk and energy requirement, automatically and in database
Recommending recipes match, and the recommending recipes matched are presented to the user, order nutritious food on line to realize.
Specifically, calculating and the scoring logic for evaluating user base nutrition condition are as follows in the step 1:
BMI=weight/(height)2, whether there is or not diseases；Wherein, BMI is body fat percentage, unit kg/m2, the unit of weight
For kg, the unit of height is m；
It is thin if BMI < 18.5；If 18.5≤BMI < 24, normally；If 24≤BMI < 28, overweight；If
BMI >=28, it is fat；
For filling in the user of body fat percentage:
Male: > 20% be it is partially fat, < 15% be it is partially thin, 15-20% is normal；Women: > 30% is partially fat, < 25%
To be partially thin, 25-30% is normal.
Specifically, in the step 2, calculating and score logic such as that automatic scoring and Nutritional Risk be the report recommends
Under:
If BMI < 18.5,3 points are obtained, age >=70 year old obtain 1 point, are otherwise 0 point；The investigation of Nutritional risk screening scale
Score addition can obtain Nutritional risk screening total score, Nutritional risk screening=0, no Nutritional Risk user；Nutritional risk screening is total
It is divided into 1-3 points, is evaluated as low middle danger Nutritional Risk user, starts dietary recommendations continued with module of making a reservation and match recommending recipes, and guide
User makes a reservation；Nutritional risk screening total score > 3, there are Nutritional Risks, are evaluated as high-risk Nutritional Risk user, and starting nutritionist is pre-
Alert module, guidance nutritionist intervene.
Specifically, the automatic logic for calculating energy requirement is as follows in the step 3:
For the user of age >=16: BMR=gender* (66+13.7*weight+500*height-6.8*age)+(1-
gender)*(655+9.6*weight+180*height-4.7*age)；
Exercise=time/60*weight* (1.66-0.016*age) * intensity；
Energy=BMR+exercise+180；
For the user of age < 16: BMR=gender* (17.5*weight+651)+(1-gender) * (12.2*
weight+746)；
Exercise=time/60*weight*intensity/2；
Energy=BMR+exercise+300；
Intensity is defaulted as 0, and all energy must not be lower than 800.
Compared with prior art, the invention has the following advantages:
The design of the invention is scientific and reasonable, easy to use, passes through the realization side of the nutritious food order system based on smart machine
The Nutritional risk screening of method can collect storing data, and according to built-in algorithm after user passes through smart machine fill substance automatically
It is automatic to calculate analysis data, and assessment classification guidance is carried out automatically, this procedure avoids nutritionist, users frequently to travel to and fro between respectively
Between a accumulation point, time and human cost are substantially reduced, more efficiently.The Nutritional risk screening covering of user is improved simultaneously
Rate is greatly promoted the improvement rate of patient's nutritional support, mitigates user's nutrition improvement expense, is conducive to push away in the art
Extensively.
The present invention is ordered by the Nutritional risk screening of its implementation and nutritious food, and user can intuitive complete and accurate
Recognize basal nutrient situation, Nutritional Risk and the recommending recipes of itself and realize self-service order nutritious food on line, to user
Health control have important facilitation, meanwhile, with adhering to for user, physical condition improve after reuse the present invention into
After row assessment idiotrophic risk, corresponding adjustment can be also made, is played the role of to user's gain feedback.
The present invention is ordered by the Nutritional risk screening and nutritious food of its implementation, all age group difference physical condition
Crowd can obtain for the Nutritional risk screening report of self-condition and nutritious food, compare more personalized has with science
Effect.
Detailed description of the invention
Fig. 1 is that the present invention is based on the system block diagrams of the nutritious food order system of smart machine.
Fig. 2 is the logic and flow chart of implementation method of the present invention.
Wherein, the corresponding title of appended drawing reference are as follows:
1- core processor, 2- Nutritional Risk module, 3- dietary recommendations continued and module of making a reservation, 4- memory module, 5- are intelligently set
Standby, 6- input module, 7- display module, 8- nutritionist's warning module.
Specific embodiment
The invention will be further described with embodiment for explanation with reference to the accompanying drawing, and mode of the invention includes but not only limits
In following embodiment.
As shown in Figure 1, the nutritious food order system provided by the invention based on smart machine,.The present invention includes at core
Device 1 is managed, with the core processor 1 by the smart machine 5 of network connection, and is connect respectively with the core processor 1
Nutritional Risk module 2, dietary recommendations continued and make a reservation module 3；The dietary recommendations continued and module 3 of making a reservation are stored with recommending recipes, institute
Mode of the smart machine 5 for by inquiry is stated to acquire user base information and basic information collected is passed through transmission of network
To the core processor 1, the core processor 1 is used to carry out handling to received basic information and by treated
Information is sent to the Nutritional Risk module 2, and the Nutritional Risk module 2 is for automatically analyzing received information
It calculates, and calculating result will be automatically analyzed and feed back to the core processor 1, the core processor 1 is automatic by what is received
Analysis result is respectively sent to the smart machine 5 and the dietary recommendations continued and module 3 of making a reservation, the dietary recommendations continued with order
Automatically analyzing of receiving is calculated result to meal module 3 and the recommending recipes that store carry out Auto-matching and by matching result in it
Be sent to the smart machine 5 by the core processor 1, the core processor 1 be connected with nutritionist's warning module 8,
And the memory module 4 of information, the smart machine 5 are described defeated equipped with input module 6 and display module 7 for storing data
Enter module 6 for realizing the human-computer interaction between user and the smart machine 5, the display module 7 is used for automatically analyzing
Calculated result, matching result and when investigating basic information survey item display, the smart machine 5 be smart phone,
Tablet computer, desktop computer or laptop.
As shown in Fig. 2, the implementation method of the nutritious food order system provided by the invention based on smart machine, including it is following
Step:
Step S1, the basic information and Nutritional risk screening scale of user are acquired in such a way that smart machine is using investigation
And basic information collected and Nutritional risk screening scale are passed through into transmission of network to core processor；
Step S2, core processor handles the basic information received and Nutritional risk screening scale, and will place
Reason result is sent to memory module and is stored, while being also communicated to Nutritional Risk module and carrying out automatically analyzing calculating, and automatic point
Analysis calculated result feeds back to core processor, this is automatically analyzed calculating result again and is respectively sent to smart machine by core processor
With dietary recommendations continued and module of making a reservation, user determines whether to order nutrition according to the calculating result that automatically analyzes that smart machine receives
Meal, if ordering, dietary recommendations continued with make a reservation module by automatically analyzing of receiving calculate the recommending recipes that are stored with it of result into
Matching result is simultaneously sent to smart machine by core processor and is presented to the user by row Auto-matching.
In the step S1, the investigation content of the basic information includes the height, gender, date of birth, body of user
Weight and body fat percentage information.In the step S1, the investigation content of the Nutritional risk screening scale includes the disease of user
State of an illness condition, weight loss situation, food-intake decline situation and exercise intensity and the information of time.
Specific questionnaire content is as follows:
Does is 1, your height? height (m).
Does is 2, your date of birth? age.
Does is 3, your gender? gender=1male/0female.
Does is 4, your weight? weight (kg).
5, whether you suffer from following disease (multiselect) ---
Without disease；
Inferior health；
Diabetes B；
Hypertension；
Constipation；
Dyslipidemia；
Gout；
Hyperuricemia；
Nephrosis；
Cardiovascular disease；
Osteoarthritis；
General malignant tumour (1)；
Hip fracture (1)；
Cirrhosis (1)；
Haemodialysis (1)；
Chronic obstructive pulmonary disease (1)；
Chronic disease has complication (1)；
Cerebral apoplexy (2)；
Hematologic malignancies (2)；
Major abdominal surgery (2)；
Severe pneumonia (2)；
Craniocerebral injury (3)；
Bone-marrow transplantation (3).
Does 6, (- 3 months 1 month) weight decline in the recent period?
A. it is；B. no；
Be (above-mentioned choosing is that occur again) if so, weight loss how many kg? (filling a vacancy, weight loss=lose weight)
Iflose weight/ (weight+lose weight) > 5%:
Weight loss be ---
A.3 in a month (1)；B.2 in a month (2)；C.1 in a month (3).
Is 7, food-intake reduced in one month?
It A. is that B. is no；
(above-mentioned choosing is that occur again) if so, appetite decline how much?
A.25%-50% (1)；
B.51%-75% (2)；
C.76%-100% (3).
Does is 8, your body fat percentage? (option)
Fat=() %.
Does is 9, my average movement duration weekly?
A 0-30 minutes；
B 30-60 minutes；
C 60-150 minutes；
D 150-300 minutes；
E 300 minutes or more.
time(min)；
Time=0A/10B/20C/40D/60E.
Do be 10, the tired degree (exercise intensity) that I moves every time? intensity (no unit)
0- stationary state (quiet, without lifting an eyebrow)；
1- and its easily (can see TV, sing)；
2- very comfortable (breathing is smooth, and can chat with people)；
3- easily (needs firmly to breathe, but still comfortable)；
4- mild (pico- to perspire, heartbeat breathing starts to accelerate)；
5- moderate (volume of perspiration increases, and heartbeat tachypnea can talk with people)；
6- a little painstaking (can be exchanged with brief sentence, breathing is slightly difficult)；
7- is relatively painstaking (can still speak, but can not sing)；
8- very painstaking (expiratory dyspnea, soaked with sweat)；
9- extremely painstaking (breathing is extremely difficult, can only say simple word, word)；
10- completely exhausted (can not breathe, can not hold on, can not speak).
In the step S2, Nutritional Risk module carries out automatically analyzing calculating and dietary recommendations continued and module of making a reservation
When with recommending recipes, comprising the following steps:
User's height, weight, the basal nutrient situation of body fat percentage information evaluation user that step 1, basis are collected into；
It calculates and scoring logic is as follows:
BMI=weight/(height)2, whether there is or not diseases；Wherein, BMI is body fat percentage, unit kg/m2, the unit of weight
For kg, the unit of height is m；
It is thin if BMI < 18.5；If 18.5≤BMI < 24, normally；If 24≤BMI < 28, overweight；If
BMI >=28, it is fat；
For filling in the user of body fat percentage:
Male: > 20% be it is partially fat, < 15% be it is partially thin, 15-20% is normal；Women: > 30% is partially fat, < 25%
To be partially thin, 25-30% is normal.
Step 2 is built according to the Nutritional risk screening scale information being collected into, progress automatic scoring and Nutritional Risk report
View；It calculates and scoring logic is as follows:
If BMI < 18.5,3 points are obtained, age >=70 year old obtain 1 point, are otherwise 0 point；The investigation of Nutritional risk screening scale
Score addition can obtain Nutritional risk screening total score, Nutritional risk screening=0, no Nutritional Risk user；Nutritional risk screening is total
It is divided into 1-3 points, is evaluated as low middle danger Nutritional Risk user, starts dietary recommendations continued with module of making a reservation and match recommending recipes, and guide
User makes a reservation；Nutritional risk screening total score > 3, there are Nutritional Risks, are evaluated as high-risk Nutritional Risk user, and starting nutritionist is pre-
Alert module, guidance nutritionist intervene.
The exercise intensity for the user that step 3, basis are collected into and time and calculated body fat percentage, it is automatic to calculate
Energy requirement；Logic is as follows:
For the user of age >=16: BMR=gender* (66+13.7*weight+500*height-6.8*age)+(1-
gender)*(655+9.6*weight+180*height-4.7*age)；
Exercise=time/60*weight* (1.66-0.016*age) * intensity；
Energy=BMR+exercise+180；
For the user of age < 16: BMR=gender* (17.5*weight+651)+(1-gender) * (12.2*
weight+746)；
Exercise=time/60*weight*intensity/2；
Energy=BMR+exercise+300；
Intensity is defaulted as 0, and all energy must not be lower than 800.
The automatic calculated body fat percentage of step 4, basis, Nutritional Risk and energy requirement, automatically and in database
Recommending recipes match, and the recommending recipes matched are presented to the user, order nutritious food on line to realize.
Implementation method of the invention is further elaborated with specific example below.
A volunteer users are randomly selected, using the present invention, are then enumerated according to the automatic calculated data in backstage as follows:
1. basal nutrient status evaluation
2. Nutritional risk screening scores
3. calculating energy requirement: 1297Kcal.
4. dietary recommendations continued and user order nutritious food.
Dietary recommendations continued recipe on the one:
User can realize self-service order nutritious food on line through the invention, by special messenger's production, dispatching.
Above-described embodiment is only one of the preferred embodiment of the present invention, should not be taken to limit protection model of the invention
It encloses, as long as that in body design thought of the invention and mentally makes has no the change of essential meaning or polishing, is solved
The technical issues of it is still consistent with the present invention, should all be included within protection scope of the present invention.
Claims (10)
1. the nutritious food order system based on smart machine, which is characterized in that including core processor (1), at the core
It manages device (1) and passes through the smart machine (5) of network connection, and the Nutritional Risk mould connecting respectively with the core processor (1)
Block (2), dietary recommendations continued and make a reservation module (3)；The dietary recommendations continued and module (3) of making a reservation are stored with recommending recipes, the intelligence
Equipment (5) acquires user base information for mode by inquiry and basic information collected is passed through transmission of network to institute
It states core processor (1), the core processor (1) is used to carry out handling to received basic information and by treated
Information is sent to the Nutritional Risk module (2), and the Nutritional Risk module (2) is used to carry out received information automatic
Analytical calculation, and calculating result will be automatically analyzed and fed back to the core processor (1), the core processor (1) will receive
To automatically analyze and calculate result and be respectively sent to the smart machine (5) and the dietary recommendations continued and make a reservation module (3), it is described
Automatically analyzing of receiving is calculated result with module (3) of making a reservation for dietary recommendations continued and the recommending recipes that store carry out automatic in it
Match and be sent to matching result the smart machine (5) by the core processor (1), the core processor (1) is even
It is connected to nutritionist's warning module (8) and for storing data memory module (4) of information.
2. the nutritious food order system according to claim 1 based on smart machine, which is characterized in that the smart machine
(5) it is equipped with input module (6) and display module (7), the input module (6) is for realizing user and the smart machine (5)
Between human-computer interaction, the display module (7) be used for automatically analyze calculate result, matching result and investigation basis
The display of survey item when information.
3. the nutritious food order system according to claim 2 based on smart machine, which is characterized in that the smart machine
It (5) is smart phone, tablet computer, desktop computer or laptop.
4. the implementation method of the nutritious food order system described in claim 1-3 any one based on smart machine, feature exist
In, comprising the following steps:
Step S1, it using the basic information and Nutritional risk screening scale for acquiring user by way of investigating and is incited somebody to action smart machine
Basic information and Nutritional risk screening scale collected passes through transmission of network to core processor；
Step S2, core processor handles the basic information received and Nutritional risk screening scale, and processing is tied
Fruit is sent to memory module and is stored, while being also communicated to Nutritional Risk module and carrying out automatically analyzing calculating, automatic analyser
It calculates result and feeds back to core processor, this is automatically analyzed calculating result again and is respectively sent to smart machine and drink by core processor
Food is recommended to determine whether order nutritious food according to the calculating result that automatically analyzes that smart machine receives with module of making a reservation, user,
If ordering, dietary recommendations continued and module of making a reservation carry out the recommending recipes that calculating result is stored with it that automatically analyze received certainly
It moves to match and matching result is sent to smart machine by core processor and be presented to the user.
5. implementation method according to claim 4, which is characterized in that in the step S1, the tune of the basic information
Look into height, gender, date of birth, weight and the body fat percentage information that content includes user.
6. implementation method according to claim 5, which is characterized in that in the step S1, the Nutritional risk screening
The investigation content of scale includes the disease event of user, weight loss situation, food-intake decline situation and exercise intensity and time
Information.
7. implementation method according to claim 6, which is characterized in that in the step S2, Nutritional Risk module is carried out
Calculating and dietary recommendations continued are automatically analyzed when matching recommending recipes with module of making a reservation, comprising the following steps:
User's height, weight, the basal nutrient situation of body fat percentage information evaluation user that step 1, basis are collected into；
The Nutritional risk screening scale information that step 2, basis are collected into, carries out automatic scoring and Nutritional Risk be the report recommends；
The exercise intensity for the user that step 3, basis are collected into and time and calculated body fat percentage, calculate energy automatically
Requirement；
Step 4, according to automatic calculated body fat percentage, Nutritional Risk and energy requirement, automatically with pushing away in database
It recommends recipe to match, and the recommending recipes matched is presented to the user, order nutritious food on line to realize.
8. implementation method according to claim 7, which is characterized in that in the step 1, evaluate user base nutrition shape
The calculating of condition and scoring logic are as follows:
BMI=weight/(height)2, whether there is or not diseases；Wherein, BMI is body fat percentage, unit kg/m2, the unit of weight is
Kg, the unit of height are m；
It is thin if BMI < 18.5；If 18.5≤BMI < 24, normally；If 24≤BMI < 28, overweight；If BMI >=
28, it is fat；
For filling in the user of body fat percentage:
Male: > 20% be it is partially fat, < 15% be it is partially thin, 15-20% is normal；Women: > 30% be it is partially fat, < 25% is inclined
Thin, 25-30% is normal.
9. implementation method according to claim 8, which is characterized in that in the step 2, automatic scoring and Nutritional Risk
The calculating and scoring logic that the report recommends are as follows:
If BMI < 18.5,3 points are obtained, age >=70 year old obtain 1 point, are otherwise 0 point；The investigation score of Nutritional risk screening scale
Addition can obtain Nutritional risk screening total score, Nutritional risk screening=0, no Nutritional Risk user；Nutritional risk screening total score is
1-3 points, it is evaluated as low middle danger Nutritional Risk user, starts dietary recommendations continued with module of making a reservation and matches recommending recipes, and guide user
It makes a reservation；Nutritional risk screening total score > 3, there are Nutritional Risks, are evaluated as high-risk Nutritional Risk user, start nutritionist's early warning mould
Block, guidance nutritionist intervene.
10. implementation method according to claim 9, which is characterized in that in the step 3, calculate energy demand automatically
The logic of amount is as follows:
For the user of age >=16: BMR=gender* (66+13.7*weight+500*height-6.8*age)+(1-
gender)*(655+9.6*weight+180*height-4.7*age)；
Exercise=time/60*weight* (1.66-0.016*age) * intensity；
Energy=BMR+exercise+180；
For the user of age < 16: BMR=gender* (17.5*weight+651)+(1-gender) * (12.2*weight+
746)；
Exercise=time/60*weight*intensity/2；
Energy=BMR+exercise+300；
Intensity is defaulted as 0, and all energy must not be lower than 800.
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| CN111564199A (en) * | 2020-05-08 | 2020-08-21 | 成都尚医信息科技有限公司 | Intelligent nutrition intervention method and terminal |
| CN111653340A (en) * | 2020-04-13 | 2020-09-11 | 江苏康爱营养科技有限责任公司 | Detection apparatus for nutritional analysis |
| CN113517053A (en) * | 2020-04-09 | 2021-10-19 | 武汉慧禹信息科技有限公司 | Intelligent diet management system and method based on patient medical advice following |
| CN114051391A (en) * | 2019-09-24 | 2022-02-15 | 松下知识产权经营株式会社 | Menu output method and menu output system |
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Application publication date: 20190528 |