CN114842950A - Fatty liver health management system and method based on comprehensive intervention of diet and exercise - Google Patents
Fatty liver health management system and method based on comprehensive intervention of diet and exercise Download PDFInfo
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- 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
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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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
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
Abstract
The invention discloses a fatty liver health management system based on diet and exercise comprehensive intervention, which comprises a standard database, a database and a database server, wherein the standard database stores food standard data and exercise standard data; the data acquisition module acquires initial weight and body composition data and initial health data of a patient; the intervention target generation module determines the intervention type and the intervention target value of the patient according to the initial health data; the intervention plan generation module calculates an intervention period according to the intervention target value and generates a first intervention plan; the data processing module calculates an initial basic energy value and a conversion energy difference value according to the initial weight and body composition data and calculates an intervention energy value corresponding to the current intervention cycle period according to the initial basic energy value and the energy difference value; the intervention prescription generating module generates an intervention prescription according to the intervention energy value, the food standard data and the exercise standard data so as to realize the sequential diet and exercise intervention on the fatty liver patient and further improve the fatty liver.
Description
Technical Field
The invention relates to the technical field of fatty liver health management, in particular to a fatty liver health management system and method based on comprehensive diet and exercise intervention.
Background
With the improvement of the living standard of people and the change of the dietary structure, the incidence of fatty liver tends to rise year by year. Because people have insufficient knowledge of fatty liver, the fatty liver is further aggravated without so-called attitude, partial patients develop liver fibrosis, liver cirrhosis and even liver cancer, the key point of fatty liver cure lies in early discovery and early treatment, and the fatty liver is known to have great relationship with a long-term bad life style, so that the early prevention of the fatty liver is mainly focused on the intervention of the life style, namely the health management of the fatty liver is very important.
The existing fatty liver intervention mode is usually ordered by a doctor, and a patient supervises and executes fatty liver intervention according to self or close relatives, at present, service systems exist on the market, and improve a diet structure and an exercise mode by recommending diet and exercise to the patient, but the service systems can only make a general prescription from the condition of most patients under the common condition, and cannot generate the prescription according to the individual cases of the patient; in addition, the improvement of fatty liver is a long-term problem, and although the existing service system can realize the diet management of patients in a short term, the actual condition of the patients is not considered, so that the patients are difficult to insist on, the overall requirements of the patients cannot be met, and the patients cannot be effectively guided to realize the individual optimal diet and exercise intervention for a long term.
Disclosure of Invention
In view of the above, the present invention aims to provide a fatty liver health management system based on comprehensive diet and exercise intervention, so as to solve the problem in the prior art that the intervention prescription is difficult to adhere to due to poor pertinence, incapability of performing gradual, long-term effective diet and exercise intervention on patients, and the like.
In order to achieve the above objects, a first aspect of the present invention provides a fatty liver health management system based on integrated diet and exercise intervention, comprising:
the standard database is used for storing food standard data and motion standard data;
the data acquisition module is used for acquiring initial weight and body composition data and initial health data of the patient;
the intervention target generation module is used for determining the intervention type of the patient according to the initial health data and determining an intervention target value based on the intervention type, the initial weight and body composition data and/or the acquired patient self-defined target;
an intervention plan generating module, configured to calculate an intervention cycle according to the intervention target value and generate a first intervention plan, where the first intervention plan at least includes at least one intervention cycle and a corresponding cycle target intervention value;
the data processing module is used for calculating an initial basic energy value according to the initial weight and body composition data, converting a cycle target intervention value corresponding to an intervention cycle in the first intervention plan into an energy difference value, and calculating to obtain an intervention energy value corresponding to the current intervention cycle according to the initial basic energy value and the energy difference value; and
and the intervention prescription generating module is used for generating an intervention prescription according to the daily intervention energy value and the food standard data and the exercise standard data in the standard database, wherein the intervention prescription comprises a diet prescription and an exercise prescription.
Further, the food standard data is stored in the standard database in the form of food exchange portions, the food exchange portions take the preset unit calorie as a counting reference to weigh the mass of each food and the content of each nutrient, wherein the nutrient at least comprises carbohydrate, protein and fat, and the food standard data at least comprises food name, food group, food category, each mass, each carbohydrate content, each protein content and each fat content;
the motion standard data is stored in the standard database in the form of a motion exchange group, the motion exchange group times the motion duration and the intensity coefficient of each group on the basis of counting energy consumption of a preset unit, and the motion standard data at least comprises a motion name, a motion group, a motion category, each group of duration and each group of intensity coefficient.
Further, the initial weight and body composition data comprises at least gender, age, height, initial weight, fat content, muscle content, and/or physical activity level; the initial health data includes at least initial examination data, dietary contraindications, and disease data.
Further, the intervention target generation module comprises:
the intervention type database is used for storing intervention types carrying fatty liver information, wherein the intervention types at least comprise timed quantitative intervention, quantitative intervention and quantitative maintenance intervention;
the intervention type matching sub-module is used for comprehensively analyzing the initial examination data and the disease data, determining fatty liver information of the patient, and inquiring and matching a corresponding intervention type in the intervention type database by taking the fatty liver information as an index; and
and the target generation submodule is used for determining an intervention target value according to the initial weight and the intervention type and/or according to the acquired custom target weight of the patient.
Further, the intervention plan generating module comprises:
an intervention cycle calculation sub-module for calculating an intervention cycle based on the intervention type, the intervention target value and/or the patient determined intervention speed;
the intervention cycle period dividing submodule is used for dividing the intervention cycle period into at least one intervention cycle period according to a preset cycle period, wherein each intervention cycle period at least comprises a quick weight loss stage, a slow weight loss stage and/or a weight loss trimming stage;
the cycle period target dividing submodule is used for dividing the intervention target value into the same number of cycle period target intervention values according to the number of the divided intervention cycle periods, and the cycle period target intervention values are sequentially decreased according to the corresponding intervention cycle periods; and
and the plan generation submodule is used for generating a first intervention plan according to the intervention cycle and the corresponding cycle target intervention value.
Further, the data processing module comprises:
the energy conversion submodule is used for converting the cycle period target intervention value corresponding to each intervention cycle period into a cycle energy difference value; and
and the energy calculation submodule is used for calculating an initial basic energy value according to the initial weight and body composition data, determining a phase intervention difference value corresponding to each phase in an intervention cycle period according to the period energy difference value, equally dividing the phase intervention difference value by taking a day as a unit to obtain a daily intervention difference value, and calculating to obtain the daily intervention energy value according to the initial basic energy value and the daily intervention difference value.
Further, the intervention prescription generating module comprises:
the prescription coefficient configuration submodule is used for configuring diet coefficients and exercise coefficients according to the initial weight and body composition data and the initial health data;
an exchange share/group calculation submodule for determining the number of food exchange shares and motion exchange groups based on the daily intervention energy value and the diet and motion coefficients;
the diet distribution submodule is used for determining the number of each meal of the food exchange shares of the three meals every day according to the preset three-meal proportion according to the number of the food exchange shares, and determining the number of the food exchange shares corresponding to each nutrient of each meal according to the preset energy supply ratio of the nutrients according to the number of each meal of the food exchange shares;
the motion distribution submodule is used for determining the group number of the motion exchange group corresponding to each motion according to the number of the motion exchange groups and a preset motion group classification ratio; and
and the prescription generation sub-module is used for matching corresponding food in the standard database according to the number of the parts of the nutrients of each meal and the initial examination data, the diet contraindication and/or the disease data to generate a diet prescription of each meal, and matching corresponding exercise in the standard database according to the group number of the exercise exchange groups corresponding to each exercise group and combining the initial examination data, the disease data and/or the physical activity level to generate a daily exercise prescription.
Furthermore, the system also comprises a data analysis module;
the data acquisition module is also used for acquiring initial diet data and initial motion data of the patient;
the data analysis module is used for analyzing the initial diet data and the initial exercise data to obtain an intervention initial value, wherein the intervention initial value comprises a diet initial value and an exercise initial value, the diet initial value at least comprises a daily diet intake initial value, an initial diet coefficient, an initial three-meal ratio and an initial nutrient energy supply ratio, and the exercise initial value at least comprises a daily exercise consumption initial value, an initial exercise coefficient and an initial exercise group ratio;
the intervention plan generating module is further used for generating a second intervention plan according to the intervention period and the intervention initial value, wherein the second intervention plan comprises an intervention adaptation period, the at least one intervention cycle period and a corresponding cycle period target intervention value;
and the data processing module is also used for calculating and obtaining the intervention energy value corresponding to the intervention cycle in the second intervention plan after the intervention adaptation period is ended.
Furthermore, the device also comprises a dynamic adjusting module;
the data acquisition module is also used for acquiring the diet data and the exercise data of the patient on the same day;
the data analysis module is also used for analyzing the daily diet data and the daily exercise data to obtain the daily actual diet intake and the daily actual exercise consumption of the patient;
the dynamic adjustment module is used for calculating the total energy of the day according to the actual dietary intake and the actual exercise consumption, calculating the total intervention difference value of the day according to the total energy of the day and the daily intervention energy value of the day, dividing the total intervention difference value into corresponding parts according to the remaining days of the current intervention cycle to obtain daily intervention difference values according to the remaining days, and superposing the daily intervention difference values to the daily intervention energy value corresponding to the remaining days of the current intervention cycle, wherein each part of daily intervention difference values are sequentially decreased.
The invention provides a fatty liver health management method based on comprehensive diet and exercise intervention, which comprises the following steps:
acquiring initial weight and body composition data and initial health data of a patient;
determining the intervention type of the patient according to the initial health data, and determining an intervention target value based on the intervention type, the initial weight and body composition data and/or the acquired patient custom target;
calculating an intervention cycle according to the intervention target value and generating a first intervention plan, wherein the first intervention plan at least comprises at least one intervention cycle and a corresponding cycle target intervention value;
calculating an initial basic energy value according to the initial weight and body composition data, converting a cycle target intervention value corresponding to an intervention cycle in the first intervention plan into an energy difference value, and calculating to obtain an intervention energy value corresponding to the current intervention cycle according to the initial basic energy value and the energy difference value;
generating an intervention prescription according to the daily intervention energy value and food standard data and exercise standard data in the standard database, wherein the intervention prescription comprises a diet prescription and an exercise prescription.
According to the invention, the data acquisition module is arranged to acquire the initial weight, body composition data and initial health data of the patient, and the intervention target of the patient is determined and the corresponding intervention plan is generated based on the initial data of the patient, so that the intervention prescription is generated in a targeted manner, and the optimal diet and exercise intervention is realized when the patient follows the intervention prescription to improve the fatty liver; and when the intervention plan is generated, the intervention plan can be divided into a plurality of intervention cycle periods, and the cycle period target intervention value corresponding to each intervention cycle period is sequentially decreased progressively, so that the patient can be intervened step by step, the body of the patient is stimulated alternately, the intervention effect is improved, and the slow weight loss or stagnation of the body of the patient caused by long-term intervention at the same speed or standard is avoided. In addition, the standard database is set, food and motion are formed into food standard data and motion standard data according to corresponding exchange rules, so that when an intervention prescription is generated, corresponding food types, weight, motion types and duration can be matched quickly, the running duration of the system can be reduced, and the calculation efficiency is improved.
Drawings
Fig. 1 is a control block diagram of a fatty liver health management system based on integrated diet and exercise intervention according to example 1 of the present invention.
Fig. 2 is a control block diagram of another embodiment of fig. 1.
Fig. 3 is a control block diagram of still another embodiment of fig. 1.
Fig. 4 is a control block diagram of the fatty liver health management system based on integrated diet and exercise intervention according to example 2 of the present invention.
Fig. 5 is a control block diagram of a fatty liver health management system based on integrated diet and exercise intervention according to embodiment 3 of the present invention.
Fig. 6 is a flowchart of a method for managing fatty liver health based on a combined diet and exercise intervention according to example 4 of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
example 1
Fig. 1 is a control block diagram of the fatty liver health management system based on comprehensive diet and exercise intervention according to the embodiment. The embodiment mainly intervenes in the life style (mainly comprising diet and exercise) of the fatty liver patient to improve the fatty liver of the patient, and as the improvement of the fatty liver is mainly to reduce the weight of the patient, it can be understood that the management system of the embodiment can be used not only for improving the fatty liver, but also for other diseases requiring intervention in a weight loss or weight gain manner, and the intervention type can be modified correspondingly. Specifically, the present embodiment includes a standard database 1, a data acquisition module 2, an intervention target generation module 3, an intervention plan generation module 4, a data processing module 5 and an intervention prescription generation module 6, through the collection of the initial weight and body composition data and the initial health data of the patient, the type of intervention required by the patient can be determined and the intervention target value can be determined, then an intervention plan is determined and generated in a targeted manner according to the intervention speed suitable for the patient, and then processing the intervention plan, converting the corresponding intervention target value into heat, determining the intervention energy of the patient at each stage and even each day when the intervention plan is executed, and finally generating an intervention prescription in a targeted manner by combining self-examination data, diet contraindications and disease data of the patient so as to improve the fatty liver according to the body level of the patient.
The standard database 1 stores food standard data and exercise standard data, and the food standard data and the exercise standard data are stored in the standard database 1 in the form of corresponding food exchange shares and exercise exchange groups. In this embodiment, the food exchange portion is used for measuring the relationship between food energy supply and weight, and the motion exchange group is used for measuring the relationship between motion energy consumption and time length.
The food exchange portions take preset unit calorie as a reference to weigh the mass of each portion of food and the content of each nutrient; the nutrients include at least carbohydrates, proteins, and fats. In specific implementation, each unit of calorie (in this embodiment, 90 kcal calorie) is regarded as one portion of food, different groups or categories of food provide different food qualities corresponding to the unit calorie, for example, 25 g for main food, 500 g for vegetables, 200 g for fruits, 50 g for meat, egg and fish, 160 g for milk, 10 g for fats and oils, etc., and the portion of food required to be taken by a patient per day can be obtained by dividing the calorie required by the patient per day by the unit calorie.
The motion exchange group counts the time length and the intensity coefficient of each group of motion on the basis of counting energy consumption of a preset unit; in specific implementation, each exercise generating one unit of energy consumption is regarded as one group, different groups or types of exercises generate different corresponding duration of one unit of energy consumption, for example, 5 minutes is required for swimming, 12 minutes is required for rope skipping, 20 minutes is required for slow walking, 10 minutes is required for fast walking, 9 minutes is required for slow running and 7 minutes is required for fast running, and the total amount of energy consumption required by the patient through exercise intervention every day is divided by the unit of energy consumption to obtain the number of exercise groups required by the patient every day.
Through the calculation of the food exchange share and the exercise exchange group, the food can be classified according to the source, the property and the like, and the exercise can be classified according to the intensity, the property and the like, and corresponding food standard data can be formed according to the carbohydrate, protein and fat content configuration contained in the food, and exercise exchange data can be formed according to the exercise intensity coefficient configuration. In this embodiment, the food standard data includes at least a food name, a food group, a food category, a per serving mass, a per serving carbohydrate content, a per serving protein content, and a per serving fat content; the motion exchange group at least comprises a motion name, a motion group, a motion category, time length of each group and an intensity coefficient of each group according to the motion standard data.
The data acquisition module 2 is used for acquiring initial weight and body composition data and initial health data of a patient; in this embodiment, the initial weight and body composition data at least includes sex, age, height, initial weight, fat content, muscle content and/or physical activity level, and the initial health data at least includes initial examination data, diet contraindications and disease data.
In the specific implementation of this embodiment, the sex, the age, the height, the fat content, the muscle content and/or the initial weight in the initial weight and the body composition data may be entered by the user, or may be collected by an external device, so as to collect the sex, the age, the height and the weight of the patient in real time, such as an identity information collecting device or a height and weight collecting device; the physical activity levels are matched according to the daily activities and occupation descriptions of the patients, and the physical activity levels at least comprise light physical activities, middle physical activities, heavy physical activities and the like. In this embodiment, for the light physical activity, the physical activity level index is 1.5, and the main matching object is to perform daily occupation mainly including sedentary (mainly manual work or light activity of legs) or long standing (mainly assembly and operation activities mainly including upper arm exertion), such as teachers, office clerks, and the like; for the middle physical activity, the index of the physical activity level is 1.75, and the main matching objects are professions mainly involving the daily pursuit of continuous actions of hands and arms, continuous actions of arms and legs, continuous actions of arms and trunk and the like, such as students, drivers, electricians, doctors and the like; for the gravity activity level, the physical activity level index is 2, and the main matching objects are professions mainly used for daily carrying out arm and trunk load work and the like, such as builders, transporters and the like. The initial examination data, diet contraindications and disease data in the initial health data can be acquired from a physical examination report or real-time examination results provided by the patient.
The intervention target generation module 3 is used for determining an intervention type of the patient according to the initial health data acquired by the data acquisition module 2, and determining an intervention target value based on the intervention type, the initial weight and body composition data and/or the acquired patient customized target. The intervention target generation module 3 comprises an intervention type database 31, an intervention type matching submodule 32 and a target generation submodule 33; wherein:
the intervention type database 31 stores intervention types carrying fatty liver information, in this embodiment, the fatty liver information includes improvement of MetS components, reversal of simple fatty liver/lean fatty liver, reduction of serum aminotransferase level, improvement of MASH (non-alcoholic steatohepatitis) and reversal of liver fibrosis, and the intervention types at least include timing quantitative intervention, quantitative intervention and quantitative maintenance intervention for different fatty liver information. Specifically, for improving the MetS component and reversing simple fatty liver/lean fatty liver, regular quantitative intervention is needed, namely, the weight is reduced by a certain weight within a certain time (for example, the weight is reduced by 3-5% within 1 year); quantitative intervention, namely, a certain weight reduction (such as 7 to 10 percent weight reduction) is required for reducing the serum aminotransferase level and improving the MASH (non-alcoholic steatohepatitis); for reversing hepatic fibrosis, quantitative maintenance intervention is required, that is, after a certain weight of body weight is reduced, the body weight is maintained for a certain time (for example, the body weight is reduced by more than 10% and maintained for 1 year).
The intervention type matching sub-module 32 is used for performing comprehensive analysis on the initial examination data and the disease data to determine the fatty liver information of the patient. In this embodiment, the fatty liver information may be obtained from the acquired initial weight and body composition data and initial health data of the patient, and then determine what type of fatty liver the patient belongs to according to the fatty liver information, so that the fatty liver information may be used as an index to query and match the corresponding intervention type in the intervention type database 31, and the fatty liver information of the patient is determined, so that the appropriate intervention type of each patient may be accurately determined, and it is advantageous to prescribe drugs according to the disease.
In the embodiment, when the method is implemented specifically, fatty liver information can be extracted from initial examination data and disease data of a patient through an information extraction model; specifically, historical examination data and historical disease data of a large number of patients and corresponding fatty liver information can be collected, the historical examination data, the historical disease data and the fatty liver information are input into an information extraction model to perform iterative training on the information extraction model, and finally, the initial examination data and the disease data of the patients collected by the data collection module 2 are input into the trained information extraction model to extract the fatty liver information.
The goal generation submodule 33 is configured to determine an intervention goal value according to the initial weight and the intervention type. In this embodiment, the intervention target value is represented as:
intervention target value ═ initial body weight X.
Wherein X is the percentage of body weight loss.
In addition, the intervention target value can be determined and obtained according to the obtained user-defined target weight of the patient, and at this time, the intervention target value is represented as:
intervention target value-patient custom target weight-initial weight.
In this embodiment, the patient-defined target weight is mainly for a patient who cannot provide initial examination data and/or disease data, or a patient who simply wants to lose weight, so as to simplify the data entry process of the patient, and further enable the patient to concentrate on the intervention prescription itself, thereby improving the compliance of the patient.
The intervention plan generating module 4 is used for calculating an intervention period according to the intervention target value generated in the intervention target generating module 3 and the scientific intervention speed, and generating a first intervention plan according to the intervention period and the intervention target value; in this embodiment, the first intervention plan comprises at least one intervention cycle and a corresponding cycle target intervention value. Specifically, the intervention plan generating module 4 includes an intervention period calculating submodule 41, an intervention cycle division submodule 42, a cycle target division submodule 43 and a plan generating submodule 44; wherein:
the intervention cycle calculation submodule 41 is arranged to calculate an intervention cycle based on the intervention type, the intervention target value and/or the patient determined intervention speed. For improvement of fatty liver of a patient, comprehensive intervention of diet and exercise is required to be performed in a long-term and gradual intervention mode, in order to enable the patient to better and maintain for a long time, the intervention target value is not required to be realized too fast, in the embodiment, the intervention speed is 0.5-1 kg/week, and the patient can determine the intervention speed according to the actual condition of the patient, so that a subsequently generated intervention prescription is more suitable for the actual condition of the patient and is favorable for maintaining.
In a specific implementation of this embodiment, for a timed intervention type (e.g., timed quantitative intervention), the intervention period is a time determined by the timed intervention type, and for a non-timed intervention type (e.g., quantitative intervention, quantitative maintenance intervention), the intervention period may be calculated by an intervention speed and an intervention target value determined by a patient, where the intervention period is expressed as:
intervention period is the intervention target value/intervention speed.
The intervention cycle period dividing submodule 42 is configured to divide the intervention cycle calculated by the intervention cycle calculating submodule 41 into at least one intervention cycle period according to a preset cycle period, where the intervention cycle period may be equal to the preset cycle period, and at this time, the intervention cycle period only includes one intervention cycle period, and of course, the intervention cycle period may also be equal to a plurality of preset cycle periods, and at this time, the intervention cycle period includes a plurality of intervention cycle periods. In this embodiment, the preset cycle period may be set to week, ten days, half month, one month, and the like according to the weight reduction speed, that is, when the intervention cycle period is one year, if the preset cycle period is set to month, twelve intervention cycle periods are included in the intervention cycle period, and according to a scientific weight reduction manner, the intervention cycle period may be further divided into a fast weight reduction period, a slow weight reduction period, and/or a weight reduction modification period, and the times of the fast weight reduction period, the slow weight reduction period, and the weight reduction modification period may be the same or different.
The cycle period target dividing submodule 43 is configured to divide the intervention target value into the same number of cycle period target intervention values according to the intervention cycle period number obtained by dividing by the intervention cycle period dividing submodule 42, and allocate the cycle period target intervention values to the corresponding intervention cycle periods. Specifically, taking the twelve intervention cycle periods as an example, the intervention target value is divided into twelve cycle period target intervention values, and the cycle period target intervention values obtained through division are respectively allocated to the corresponding intervention cycle periods.
As a preferable mode of this embodiment, when dividing the intervention target, the intervention target value is divided into twelve cycle period target intervention values by an arithmetic decreasing manner, that is, the twelve cycle period target intervention values sequentially decrease according to the corresponding intervention cycle periods, so that the weight loss number is large when the early-stage weight base number is large, and the weight loss number is small when the later-stage weight base number is small, which is in accordance with scientific weight loss. It is understood that, in some other embodiments, the difference between the twelve cycle period target intervention values may be decreased in a manner other than the initial difference decrease, so as to obtain the corresponding twelve cycle period target intervention values.
The plan generating submodule 44 is configured to generate a first intervention plan according to the intervention cycle obtained by dividing by the intervention cycle dividing submodule 42 and the cycle target intervention values which are obtained by dividing by the cycle target dividing submodule 43 and correspond to the intervention cycle one to one.
The data processing module 5 is configured to calculate an initial basis energy value according to the initial weight and body composition data acquired by the data acquisition module 2, convert each cycle period target intervention value into an energy difference value according to a cycle period target intervention value corresponding to each intervention cycle period in the first intervention plan generated by the intervention plan generation module 4, and calculate an intervention energy value corresponding to the current intervention cycle period according to the initial basis energy value and the energy difference value. Specifically, the data processing module 5 includes an energy conversion submodule 51 and an energy calculation submodule 52; wherein:
the energy conversion submodule 51 is configured to convert the cycle period target intervention value corresponding to each intervention cycle period generated in the intervention plan generation module 4 into a cycle energy difference value; the cycle energy difference is the amount of energy that needs to be expended to reach the cycle target intervention value (i.e., the amount of weight loss corresponding to the cycle target intervention value) during the intervention cycle. In this embodiment, since weight loss can be mainly expressed as fat loss, and the energy consumption for losing one kilogram of fat (or body weight) is about nine kcal, the conversion coefficient between the cycle target intervention value (weight loss) and the energy difference value can be calculated to be 9 kcal/g, and the cycle target intervention value is converted into the corresponding energy difference value.
The energy calculating submodule 52 is configured to calculate an initial base energy value of the patient according to the initial weight and body composition data acquired by the data acquiring module 2. In this embodiment, the initial base energy value is calculated by using the FAO/WHO/UNU, the european union, australia, japan, and southeast asia, and the national revised energy DRI formula:
TEE＝BEE*BW*PAL (1)
wherein: TEE is the patient's initial basal energy value in kcal/d (where kcal is kcal and d is day); BEE is the basal metabolic energy expenditure of a patient, which is related to the sex and age of the patient and is obtained by a table look-up (see Table 1 below) in kcal/kg. d; BW is the body weight of the patient in kg; PAL is the physical activity level coefficient (the specific value refers to the description of the data acquisition module 2 in this embodiment).
TABLE 1
The energy calculation submodule 52 is further configured to, according to the periodic energy difference obtained through conversion by the energy conversion submodule 51, allocate the periodic energy difference to each of the fast weight loss stage, the slow weight loss stage, and the weight loss trimming stage in the intervention cycle according to a ratio (e.g., 2:1:0) of the fast weight loss stage, the slow weight loss stage, and the weight loss trimming stage in the intervention cycle to form a stage energy difference of each stage, and then equally divide the stage energy value into four days by taking a day as a unit to form a daily intervention difference, where the daily intervention difference is an amount of energy that needs to be consumed by each day to reach a target intervention value in the intervention cycle, and finally calculate a daily intervention energy value according to the daily intervention difference and the initial base energy value:
daily intervention energy value-initial basis energy value-daily intervention difference.
Therefore, an energy gap (namely a daily intervention difference) is manufactured on the basis of the original diet and exercise so as to achieve the purpose of losing weight.
The intervention prescription generating module 6 is configured to generate an intervention prescription according to the daily intervention energy value calculated by the data processing module 5 and the food standard data and the exercise standard data in the standard database 1, where the intervention prescription includes a diet prescription and an exercise prescription in this embodiment. The intervention prescription generating module 6 comprises a prescription coefficient configuration sub-module 61, an exchange share/group calculation sub-module 62, a diet distribution sub-module 63, a sport distribution sub-module 64 and a prescription generating sub-module 65; wherein:
the prescription coefficient configuration submodule 61 is configured to configure a diet coefficient and/or a motion coefficient according to the initial weight and body composition data and the initial health data of the patient acquired by the data acquisition module 2, the diet coefficient and the motion coefficient are used for representing the relationship between diet intervention and motion intervention of the patient on the same day, the diet coefficient and the motion coefficient are both set as standard values when being 1, namely the diet coefficient and the motion coefficient are suitable for the cooperation of the diet intervention and the motion intervention of most patients, and for the special condition of some patients, the corresponding diet coefficient and the motion coefficient are about 1 and are in direct proportion, namely the corresponding motion energy consumption of the patient is correspondingly increased when the calorie taken by the diet on the same day is increased, so as to ensure that the daily intervention energy value is reached, and vice versa. Specifically, if the daily intervention energy value of the patient is Q, and the daily dietary intake calorie of the patient is Q at the standard value F Energy consumed by exercise is Q S When the motion coefficients are all 1, i.e. Q ═ Q F +Q S If the exercise coefficient is set to 2 at this time, the diet coefficient is correspondingly set to (Q) S +Q F )/Q F If the diet coefficient is set to 1.2 at this time, the exercise coefficient is: 0.2Q F /Q S +1, analogize in turn, make the patient through the caloric intake of diet and energy consumed through the exercise each day can be adjusted flexibly according to the particular situation, in order to improve the pertinence of the intervention prescription.
The exchange share/group calculation submodule 62 is configured to determine the number of food exchange shares and exercise exchange groups according to the daily intervention energy value calculated by the data processing module 5 and the diet coefficient and exercise coefficient configured by the prescription coefficient configuration submodule 61. For easy understanding, the present embodiment is described by taking the diet coefficient and the exercise coefficient both as 1, and if the daily intervention energy value of the patient is Q, the patient passes through diet every dayThe caloric intake is Q F Energy consumed by exercise is Q S Determining preset unit heat and preset unit energy consumption determined by the motion exchange group according to the food exchange shares, wherein the number of the food exchange shares is N1-Q F And/90, the number of the motion exchange groups is N2 ═ Q S /90。
The diet distribution submodule 63 is configured to determine the number of food exchange shares N1 according to the number of food exchange shares determined by the exchange share/group calculation submodule 62, the number of each meal of three meals per day according to a preset three-meal ratio, and determine the number of food exchange shares corresponding to each nutrient of each meal according to the preset energy ratio of the nutrient according to each meal number of the food exchange shares. Specifically, in this embodiment, according to a preset three-meal ratio (i.e., a three-meal calorie distribution ratio) for breakfast: lunch: 1:2:2, namely the number of the food exchange portions corresponding to breakfast is N B 1/5 × N1, the number of food exchange portions for lunch is N L 2/5 × N1, and the number of food exchange portions for the dinner is N D 2/5 × N1; and then according to the preset energy ratio of the three nutrients, carbohydrates: protein: fat 60:30:10, the fraction of carbohydrate, protein and fat per meal was determined in combination with the fraction of food exchange portions per meal.
The motion allocation submodule 64 is configured to determine, according to the number N2 of the motion exchange groups determined by the exchange share/group calculation submodule 62, the group number of the motion exchange group corresponding to each motion according to a preset motion group classification ratio (e.g., aerobic motion: anaerobic motion: impedance training: 1:0.5), specifically referring to the number allocation manner of the food exchange shares, which is not described in detail in this embodiment.
The prescription generation sub-module 65 is configured to generate a diet prescription for each meal according to the number of the nutrients of each meal determined by the diet distribution sub-module 63, and by combining the initial examination data, diet contraindications and/or disease data to match the corresponding food in the standard database 1, and generate a daily exercise prescription according to the number of exercise exchange groups corresponding to each exercise group of the exercise distribution sub-module 64, and by combining the initial examination data, disease data and/or physical activity level to match the corresponding exercise in the standard database 1. In the specific implementation of the embodiment, the preference of the patient for food or exercise can be collected in advance through the data collection module 2, so that when the intervention prescription is generated, the food or exercise with higher preference of the patient can be preferably matched, which is further beneficial to improving the adherence of the user, and further improving the intervention effect.
As shown in fig. 2, as a preferred mode of the embodiment, a compliance module 7 is further included for improving the compliance of the patient by interacting with the patient during the execution of the intervention prescription. Specifically, the compliance module 7 includes a prompt sub-module 71, an incentive sub-module 72, an instruction sending sub-module 73 and an interaction sub-module 74; wherein: the prompt submodule 71 is configured to generate a prompt message within a preset time to prompt the patient to upload diet data and daily exercise data of each meal. The motivation sub-module 72 is used to automatically present the patient with motivation and periodic summary reports based on the dietary data and exercise data uploaded by the patient to improve patient compliance with the system. The instruction sending submodule 73 is configured to send an interaction instruction to the patient. The interaction submodule 74 is configured to collect responses from the patient in response to interaction commands initiated by the system, and to provide incentives to the patient upon completion, etc., to further improve patient compliance with the system.
As shown in fig. 3, as another preferred mode of the present embodiment, the present invention further includes a management terminal 8, the standard database 1, the data acquisition module 2, the intervention target generation module 3, the intervention plan generation module 4, the data processing module 5, and the intervention prescription generation module 6 may be embedded in the management terminal 8 in an application software manner, and the management terminal 8 may be any modern intelligent electronic device that can be used for high-speed calculation, numerical calculation, and logic calculation, such as a desktop computer, a mobile computer, a tablet computer, and the like, and further has a storage and memory function, and can be operated according to a program to automatically process mass data at high speed. Meanwhile, a data acquisition terminal in communication connection with the management terminal 8 can be further arranged for detecting and transmitting body data corresponding to the patient to the management terminal 8 so as to be acquired by the data acquisition module 2; for the embodiment, the data acquisition terminal can be a weight scale, a body fat scale and any other device capable of detecting body data of a patient.
The fatty liver health management system based on diet and exercise comprehensive intervention of the embodiment collects initial data of a patient through the data collection module 2, determines an intervention target of the patient based on the initial data of the patient and generates a corresponding intervention plan, so that an intervention prescription is generated in a targeted manner, the patient can realize optimal diet and exercise intervention when the fatty liver is improved by following the intervention prescription, and the patient can be subjected to progressive intervention, so that the adaptability of the patient can be effectively improved, and the intervention effect can be improved.
Example 2
Fig. 4 is a control block diagram of the fatty liver health management system based on integrated diet and exercise intervention according to this embodiment. The fatty liver health management system based on diet and exercise integrated intervention of the embodiment comprises a standard database 1, a data acquisition module 2, an intervention target generation module 3, an intervention plan generation module 4, a data processing module 5 and an intervention prescription generation module 6 which have the same or similar functions and structures as those of the embodiment 1. The difference between the present embodiments is: the embodiment further includes a data parsing module 9.
In this embodiment, the data collection module 2 is further configured to collect initial diet data and initial exercise data of the patient.
The data analysis module 9 is configured to analyze the initial diet data and the initial exercise data acquired by the data acquisition module 2 to obtain an intervention initial value, in this embodiment, the intervention initial value includes a diet initial value and an exercise initial value, the diet initial value at least includes a daily diet intake initial value, an initial diet coefficient, an initial three-meal ratio and an initial nutrient energy supply ratio, and the exercise initial value at least includes a daily exercise consumption initial value, an initial exercise coefficient and an initial exercise group ratio. The intervention initial value is used as initial data of diet and exercise before the intervention is performed on the patient, so that the set daily intervention energy value, diet coefficient, three meal ratio, nutrient energy supply ratio, daily exercise consumption value, exercise coefficient and exercise group ratio are gradually approached on the basis of the initial data, and the adaptability of the user is further improved.
In this regard, in this embodiment, the intervention plan generating module 4 is further configured to generate a second intervention plan according to the intervention cycle and the intervention initial value, where the second intervention plan includes an intervention adaptation period, the at least one intervention cycle and a corresponding cycle target intervention value; the intervention adaptation period is a stage of gradually adjusting the eating habits and the exercise habits of the patient to scientific eating habits and exercise habits so as to realize the gradual and gradual intervention on the diet and exercise of the patient. In this embodiment, the description of the intervention cycle refers to the description related to embodiment 1, and this embodiment is not described in detail.
The data processing module 5 is further configured to calculate, after the intervention adaptation period ends, an intervention energy value corresponding to the intervention cycle period in the second intervention plan. In this embodiment, the specific method, based on the intervention energy value corresponding to the intervention cycle in the second intervention plan, of the data processing module 5 refers to the related description of embodiment 1, and details are not repeated in this embodiment.
The fatty liver health management system based on diet and exercise comprehensive intervention of this embodiment through setting up data analysis module 9, can be based on diet data and motion data before diet and exercise intervention are carried out to the patient to increase an intervention adaptation period on the basis of intervening, make the patient can be adjusted to the diet habit and the motion habit of intervening gradually by original diet habit and motion habit, and then realize progressive intervention, thereby improve the intervention effect.
Example 3
Fig. 3 is a control block diagram of the fatty liver health management system based on comprehensive diet and exercise intervention according to the embodiment. The fatty liver health management system based on diet and exercise integrated intervention of the embodiment comprises a standard database 1, a data acquisition module 2, an intervention target generation module 3, an intervention plan generation module 4, a data processing module 5 and an intervention prescription generation module 6 which have the same or similar functions and structures as those of the embodiment 1, and a data analysis module 9 which has the same or similar functions and structures as those of the embodiment 1. The difference between the present embodiments is: the present embodiment further includes a dynamic adjustment module 10.
In this embodiment, the data acquisition module 2 is further configured to acquire diet data and exercise data of the patient on the same day. The data analysis module 9 is further configured to analyze the daily diet data and the daily exercise data to obtain the daily actual diet intake and the daily actual exercise consumption of the patient.
The dynamic adjustment module 10 is configured to calculate a total energy of the current day according to the actual dietary intake and the actual exercise consumption, calculate a total intervention difference value of the current day according to the total energy of the current day and a daily intervention energy value of the current day, divide the total intervention difference value into corresponding parts according to the remaining days of the current intervention cycle to obtain daily intervention difference values, and superimpose the daily intervention difference values onto the daily intervention energy value corresponding to the remaining days of the current intervention cycle, where in this embodiment, the daily intervention difference values of each part are sequentially decreased. Specifically, if the daily intervention energy value is Q, the total intervention difference value on the day is Q W (the total difference of intervention is Q) W Either positive or negative) the remaining number of days of the current intervention cycle is 5 days, the total difference in intervention is Q W Dividing into five parts according to an equal difference decreasing mode to obtain daily intervention difference value Q W1 ～Q W5 Then the daily intervention difference Q W1 ～Q W5 Superposing the daily intervention energy values of the remaining 5 days, namely respectively representing the daily intervention energy values of the remaining 5 days in the intervention cycle as Q + Q W1 、Q+Q W2 、Q+Q W3 、Q+Q W4 、Q+Q W5 Finally, the daily intervention energy value Q + Q of 5 days remains W1 、Q+Q W2 、Q+Q W3 、Q+Q W4 、Q+Q W5 And updating the intervention plan corresponding to the value.
According to the fatty liver health management system based on diet and exercise comprehensive intervention, the dynamic adjustment module 10 is arranged, and the daily intervention difference value in the remaining days of the current intervention cycle is dynamically adjusted according to the daily actual diet intake and the actual exercise consumption of the patient, so that the cycle intervention value in the intervention cycle can be realized as expected, and the intervention effect is further ensured.
Example 4
Fig. 4 is a flowchart of the method for managing fatty liver health based on the combined diet and exercise intervention according to this embodiment. The method for managing fatty liver health based on comprehensive diet and exercise intervention of the present example is implemented based on the system for managing fatty liver health based on comprehensive diet and exercise intervention of the present example 1. The embodiment comprises the following steps:
s1: patient initial data is acquired.
Specifically, acquiring initial weight and body composition data and initial health data of a patient; in this embodiment, the initial weight and body composition data at least includes sex, age, height, initial weight and/or physical activity level, and the initial health data at least includes initial examination data, diet contraindications and disease data.
S2: a patient intervention type is determined and an intervention target value is determined.
Specifically, the initial examination data and the disease data are comprehensively analyzed to determine the fatty liver information of the patient, and then the type of the fatty liver to which the patient belongs is determined according to the fatty liver information, so that the corresponding intervention type is matched, and finally the intervention target value is determined according to the initial weight and the intervention type
S3: a first intervention plan is generated.
Specifically, an intervention period is calculated according to the intervention type, the intervention target value and/or the intervention speed determined by the patient, the intervention period calculated by the intervention period calculation sub-module 41 is divided into at least one intervention cycle according to a preset cycle period, the intervention target value is divided into the same number of cycle target intervention values according to the number of the intervention cycle periods obtained by division, the cycle target intervention values are distributed to the corresponding intervention cycle periods, and finally a first intervention plan is generated according to the intervention cycle periods obtained by division and the cycle target intervention values corresponding to the intervention cycle periods one to one.
S4: an initial base energy value and an intervention energy value are calculated.
Specifically, an initial basic energy value is calculated according to the initial weight and body composition data, a cycle period target intervention value corresponding to each intervention cycle period in the first intervention plan is converted into an energy difference value according to the cycle period target intervention value, and an intervention energy value corresponding to the current intervention cycle period is calculated according to the initial basic energy value and the energy difference value.
S5: an intervention prescription is generated.
In particular, an intervention prescription is generated based on the daily intervention energy value and food standard data and exercise standard data in a standard database 1, which in this embodiment includes a diet prescription and an exercise prescription.
According to the fatty liver health management method based on diet and exercise comprehensive intervention, the initial data of the patient is collected, so that an intervention prescription suitable for the patient can be generated in a targeted manner based on the initial data of the patient, and the fatty liver of the patient is improved through diet and exercise comprehensive intervention.
Claims (10)
1. Fatty liver health management system based on diet and motion comprehensive intervention, characterized by comprising:
the standard database is used for storing food standard data and motion standard data;
the data acquisition module is used for acquiring initial weight and body composition data and initial health data of the patient;
the intervention target generation module is used for determining the intervention type of the patient according to the initial health data and determining an intervention target value based on the intervention type, the initial weight and body composition data and/or the acquired patient self-defined target;
an intervention plan generating module, configured to calculate an intervention cycle according to the intervention target value and generate a first intervention plan, where the first intervention plan at least includes at least one intervention cycle and a corresponding cycle target intervention value;
the data processing module is used for calculating an initial basic energy value according to the initial weight and body composition data, converting a cycle target intervention value corresponding to an intervention cycle in the first intervention plan into an energy difference value, and calculating to obtain an intervention energy value corresponding to the current intervention cycle according to the initial basic energy value and the energy difference value; and
and the intervention prescription generating module is used for generating an intervention prescription according to the daily intervention energy value and the food standard data and the exercise standard data in the standard database, wherein the intervention prescription comprises a diet prescription and an exercise prescription.
2. The system for managing fatty liver health based on combined diet and exercise intervention according to claim 1, wherein the food standard data is stored in the standard database in the form of food exchange servings weighing the mass of each serving and the content of each nutrient on a count basis of a preset unit calorie, wherein the nutrients include at least carbohydrate, protein and fat, and the food standard data includes at least food name, food group, food category, each serving mass, each serving carbohydrate content, each serving protein content and each serving fat content;
the motion standard data is stored in the standard database in the form of a motion exchange group, the motion exchange group times the motion duration and the intensity coefficient of each group on the basis of counting energy consumption of a preset unit, and the motion standard data at least comprises a motion name, a motion group, a motion category, each group of duration and each group of intensity coefficient.
3. The integrated diet and exercise intervention-based fatty liver health management system of claim 2, wherein the initial weight and body composition data comprises at least gender, age, height, initial weight, fat content, muscle content, and/or physical activity level; the initial health data includes at least initial examination data, dietary contraindications, and disease data.
4. The integrated diet and exercise intervention-based fatty liver health management system of claim 3, wherein the intervention goal generating module comprises:
the intervention type database is used for storing intervention types carrying fatty liver information, wherein the intervention types at least comprise timed quantitative intervention, quantitative intervention and quantitative maintenance intervention;
the intervention type matching sub-module is used for comprehensively analyzing the initial examination data and the disease data, determining fatty liver information of the patient, and inquiring and matching a corresponding intervention type in the intervention type database by taking the fatty liver information as an index; and
and the target generation submodule is used for determining an intervention target value according to the initial weight and the intervention type and/or according to the acquired custom target weight of the patient.
5. The integrated dietary and exercise intervention-based fatty liver health management system of claim 4, wherein the intervention plan generation module comprises:
an intervention cycle calculation sub-module for calculating an intervention cycle based on the intervention type, the intervention target value and/or the patient determined intervention speed;
the intervention cycle period dividing submodule is used for dividing the intervention cycle period into at least one intervention cycle period according to a preset cycle period, wherein each intervention cycle period at least comprises a quick weight loss stage, a slow weight loss stage and/or a weight loss trimming stage;
the cycle period target dividing submodule is used for dividing the intervention target value into the same number of cycle period target intervention values according to the number of the divided intervention cycle periods, and the cycle period target intervention values are sequentially decreased according to the corresponding intervention cycle periods; and
and the plan generation submodule is used for generating a first intervention plan according to the intervention cycle and the corresponding cycle target intervention value.
6. The integrated dietary and exercise intervention-based fatty liver health management system of claim 5, wherein the data processing module comprises:
the energy conversion submodule is used for converting the cycle period target intervention value corresponding to each intervention cycle period into a cycle energy difference value; and
and the energy calculation submodule is used for calculating an initial basic energy value according to the initial weight and body composition data, determining a phase intervention difference value corresponding to each phase in an intervention cycle period according to the period energy difference value, equally dividing the phase intervention difference value by taking a day as a unit to obtain a daily intervention difference value, and calculating to obtain the daily intervention energy value according to the initial basic energy value and the daily intervention difference value.
7. The integrated dietary and exercise intervention-based fatty liver health management system of claim 6, wherein the intervention prescription generation module comprises:
the prescription coefficient configuration submodule is used for configuring diet coefficients and exercise coefficients according to the initial weight and body composition data and the initial health data;
an exchange share/group calculation submodule for determining the number of food exchange shares and motion exchange groups based on the daily intervention energy value and the diet and motion coefficients;
the diet distribution submodule is used for determining the number of each meal of the food exchange shares of the three meals every day according to the preset three-meal proportion according to the number of the food exchange shares, and determining the number of the food exchange shares corresponding to each nutrient of each meal according to the preset energy supply ratio of the nutrients according to the number of each meal of the food exchange shares;
the motion distribution submodule is used for determining the group number of the motion exchange group corresponding to each motion according to the number of the motion exchange groups and a preset motion group classification ratio; and
and the prescription generation sub-module is used for matching corresponding food in the standard database according to the number of the parts of the nutrients of each meal and the initial examination data, the diet contraindication and/or the disease data to generate a diet prescription of each meal, and matching corresponding exercise in the standard database according to the group number of the exercise exchange groups corresponding to each exercise group and combining the initial examination data, the disease data and/or the physical activity level to generate a daily exercise prescription.
8. The integrated dietary and exercise intervention-based fatty liver health management system of claim 2, further comprising a data parsing module;
the data acquisition module is also used for acquiring initial diet data and initial motion data of the patient;
the data analysis module is used for analyzing the initial diet data and the initial exercise data to obtain an intervention initial value, wherein the intervention initial value comprises a diet initial value and an exercise initial value, the diet initial value at least comprises a daily diet intake initial value, an initial diet coefficient, an initial three-meal ratio and an initial nutrient energy supply ratio, and the exercise initial value at least comprises a daily exercise consumption initial value, an initial exercise coefficient and an initial exercise group ratio;
the intervention plan generating module is further used for generating a second intervention plan according to the intervention period and the intervention initial value, wherein the second intervention plan comprises an intervention adaptation period, the at least one intervention cycle period and a corresponding cycle period target intervention value;
and the data processing module is also used for calculating and obtaining the intervention energy value corresponding to the intervention cycle in the second intervention plan after the intervention adaptation period is ended.
9. The integrated dietary and exercise intervention-based fatty liver health management system of claim 8, further comprising a dynamic adjustment module;
the data acquisition module is also used for acquiring the diet data and the exercise data of the patient on the same day;
the data analysis module is also used for analyzing the daily diet data and the daily exercise data to obtain the daily actual diet intake and the daily actual exercise consumption of the patient;
the dynamic adjustment module is used for calculating the total energy of the day according to the actual dietary intake and the actual exercise consumption, calculating the total intervention difference value of the day according to the total energy of the day and the daily intervention energy value of the day, dividing the total intervention difference value into corresponding parts according to the remaining days of the current intervention cycle to obtain daily intervention difference values according to the remaining days, and superposing the daily intervention difference values to the daily intervention energy value corresponding to the remaining days of the current intervention cycle, wherein each part of daily intervention difference values are sequentially decreased.
10. The fatty liver health management method based on comprehensive intervention of diet and exercise is characterized by comprising the following steps:
acquiring initial weight and body composition data and initial health data of a patient;
determining the intervention type of the patient according to the initial health data, and determining an intervention target value based on the intervention type, the initial weight and body composition data and/or the acquired patient custom target;
calculating an intervention cycle according to the intervention target value and generating a first intervention plan, wherein the first intervention plan at least comprises at least one intervention cycle and a corresponding cycle target intervention value;
calculating an initial basic energy value according to the initial weight and body composition data, converting a cycle target intervention value corresponding to an intervention cycle in the first intervention plan into an energy difference value, and calculating to obtain an intervention energy value corresponding to the current intervention cycle according to the initial basic energy value and the energy difference value;
generating an intervention prescription according to the daily intervention energy value and food standard data and exercise standard data in the standard database, wherein the intervention prescription comprises a diet prescription and an exercise prescription.
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