WO2022193676A1

WO2022193676A1 - Method and apparatus for generating user portrait, and storage medium and electronic device

Info

Publication number: WO2022193676A1
Application number: PCT/CN2021/128263
Authority: WO
Inventors: 王磊; 魏绎郦; 黄迪; 李林峰
Original assignee: 北京懿医云科技有限公司
Priority date: 2021-03-16
Filing date: 2021-11-02
Publication date: 2022-09-22
Also published as: CN113035317A

Abstract

A method and apparatus for generating a user portrait, and a storage medium and an electronic device, which relate to the technical field of big data processing. The method comprises: determining user labels of a target user in a plurality of different dimensions according to disease information and daily life information; determining the current exercise schedule and the current diet schedule of the target user according to the user labels in the different dimensions and daily behavior information of the target user; constructing a target schedule according to the current exercise schedule and the current diet schedule, and generating a user portrait of the target user according to the target schedule, a preset exercise category and a food category; and matching a standard diet scheme and a standard exercise scheme for the target user according to the user portrait, and sending the standard diet scheme and the standard exercise scheme to a terminal device of the target user. The accuracy of a standard diet scheme and a standard exercise scheme is improved.

Description

User portrait generation method and device, storage medium, and electronic device

CROSS-REFERENCE TO RELATED APPLICATIONS

This application requires the application number 202110281263.4 to be submitted on March 16, 2021 and the name is "User The priority of the Chinese patent application for the portrait generation method and device, storage medium, and electronic equipment”, the Chinese patent application The entire contents of please are incorporated herein by reference in their entirety.

technical field

Embodiments of the present invention relate to the technical field of big data processing, and in particular, to a user portrait generation method, a user portrait generation device, a computer-readable storage medium, and an electronic device.

Background technique

Diabetes mellitus is a common chronic non-communicable disease, a clinical syndrome caused by the interaction of genetic and environmental factors, and a lifelong disease. Among them, the management of diabetes, one of the main ways is to manage the patient's blood sugar.

In addition to the intervention of drugs, the management methods of blood sugar mainly include exercise management and diet management. In some methods of exercise management and diet management, a corresponding exercise plan and a diet plan are formulated for the user directly according to the user's own body mass index and combined with the existing medical knowledge.

SUMMARY OF THE INVENTION

According to one aspect of the present disclosure, a method for generating a user portrait is provided, comprising:

Acquiring disease information and daily life information of the target user, and determining user labels of the target user in multiple different dimensions according to the disease information and daily life information;

Determine the current exercise plan and the current diet plan of the target user according to the user tags on each of the different dimensions and the daily behavior information of the target user;

Build a target plan according to the current exercise plan and the current diet plan, and generate a user portrait of the target user according to the goal plan, preset sports categories and food categories;

Match a standard diet plan and a standard exercise plan for the target user according to the user portrait, and send the standard diet plan and standard exercise plan to the terminal device where the target user is located.

According to one aspect of the present disclosure, there is provided an apparatus for generating user portraits, comprising:

a user label calculation module, used to obtain disease information and daily life information of a target user, and determine user labels of the target user in multiple different dimensions according to the disease information and daily life information;

a plan table calculation module, configured to determine the current exercise plan table and the current diet plan table of the target user according to the user labels on each of the different dimensions and the daily behavior information of the target user;

A user portrait generation module, configured to construct a target plan according to the current exercise plan and the current diet plan, and generate a user portrait of the target user according to the goal plan, preset sports categories and food categories;

A plan matching module, configured to match a standard diet plan and a standard exercise plan for the target user according to the user portrait, and send the standard diet plan and the standard exercise plan to the terminal device where the target user is located.

According to one aspect of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements any one of the above-mentioned methods for generating a user portrait.

According to one aspect of the present disclosure, there is provided an electronic device, comprising:

processor; and

a memory for storing executable instructions for the processor;

Wherein, the processor is configured to execute any one of the user portrait generation methods described above by executing the executable instructions.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and for those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort. In the attached image:

FIG. 1 schematically shows a flowchart of a method for generating a user portrait according to an exemplary embodiment of the present disclosure.

FIG. 2 schematically shows an example diagram of calculating a resting metabolic rate according to an exemplary embodiment of the present disclosure.

Fig. 3 schematically shows a method for determining the current exercise plan and the current diet plan of the target user according to the user tags on each of the different dimensions and the daily behavior information of the target user according to an exemplary embodiment of the present disclosure method flow chart.

FIG. 4 schematically shows an example diagram of calculation of a user's planned heart rate according to an exemplary embodiment of the present disclosure.

FIG. 5 schematically shows a construction of a target plan according to the current exercise plan and the current diet plan according to an exemplary embodiment of the present disclosure, and according to the goal plan, a preset sports category and a food category, generating The method flowchart of the user portrait of the target user.

FIG. 6 schematically shows a flowchart of another method for generating a user portrait according to an exemplary embodiment of the present disclosure.

FIG. 7 schematically shows a block diagram of an apparatus for generating a user portrait according to an exemplary embodiment of the present disclosure.

FIG. 8 schematically shows an electronic device for implementing the above-mentioned method for generating a user portrait according to an exemplary embodiment of the present disclosure.

Detailed ways

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments, however, can be embodied in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repeated descriptions will be omitted. Some of the block diagrams shown in the figures are functional entities that do not necessarily necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

Diabetes mellitus is a common chronic non-communicable disease, a clinical syndrome caused by the interaction of genetic and environmental factors, and a lifelong disease. Diabetes is caused by the inability of the pancreas to secrete insulin normally, or the dysfunction of insulin. In addition to family genetic factors, in recent years, the human body has been surrounded by high-calorie diets such as takeaways and snacks for a long time, coupled with the combined effect of factors such as the lack of exercise caused by the fat house culture, and the poor psychological state caused by occupational pressure, diabetes The incidence is showing a continuous upward trend, and its prevention and rehabilitation have become an extremely urgent task. The management of diabetes, one of the main ways is the management of patients' blood sugar.

Blood sugar management formulates exercise and diet management plans based on a comprehensive evaluation of personal health status, psychological status, diet status and lifestyle, and urges patients to implement them. Through the effect evaluation, the management plan is adjusted and implemented again, so as to achieve the purpose of long-term fat reduction and hypoglycemic reduction. In addition to the intervention of drugs, the management methods of blood sugar mainly include exercise management and diet management. Among them, the purpose of diet management is to quantify the content of the three major nutrients in the diet, the calorie intake, the proportion of three meals, the proportion and quantity of trace elements, etc. The purpose of exercise management is to quantify exercise intensity, exercise time, exercise frequency, etc. elements. Clinical practice shows that the effect of blood sugar management through the combination of exercise management and diet management is particularly significant.

This exemplary embodiment first provides a method for generating user portraits, which can run on a server, server cluster, or cloud server, etc. Of course, those skilled in the art can also run the method of the present invention on other platforms as required. This example This is not specifically limited in the exemplary embodiment. Referring to Figure 1, the user portrait generation method may include the following steps:

Step S110. Obtain disease information and daily life information of the target user, and determine user tags of the target user in multiple different dimensions according to the disease information and daily life information;

Step S120. Determine the current exercise plan and the current diet plan of the target user according to the user labels on each of the different dimensions and the daily behavior information of the target user;

Step S130. Build a target schedule according to the current exercise schedule and the current diet schedule, and generate a user portrait of the target user according to the target schedule, preset sports categories and food categories;

Step S140. Match a standard diet plan and a standard exercise plan for the target user according to the user portrait, and send the standard diet plan and standard exercise plan to the terminal device where the target user is located.

In the above user portrait generation method, on the one hand, by obtaining the disease information and daily life information of the target user, and according to the disease information and daily life information, the user labels of the target user in multiple different dimensions are determined; The user tag and the daily behavior information of the target user, determine the current exercise plan and the current diet plan of the target user; then construct the goal plan according to the current exercise plan and the current diet plan, and according to the goal plan, preset Sports category and food category, generate the user portrait of the target user; finally, match the standard diet plan and standard exercise plan for the target user according to the user portrait, and send the standard diet plan and standard exercise plan to the terminal device where the target user is located. In the process of user portrait, the user labels in multiple different dimensions of the target user are considered at the same time, and the user label is calculated according to the disease information and daily life information, thus solving the problem in the prior art due to the lack of combination of the user's disease. information and daily life information, so that the user portrait cannot be generated according to the user's disease information and daily life information, so that the accuracy of the user portrait is low, which improves the accuracy of the user portrait; on the other hand, it solves the problem of the existing technology. Because only based on the user's own body mass index and existing medical knowledge, there is no user's feedback information as a label, which makes the exercise plan and diet plan less accurate; on the other hand, in the current exercise plan table and the current diet When planning the table, the daily behavior information is considered, that is, the feedback information of the user on the standard diet plan and the standard exercise plan is taken into account, which further improves the accuracy of the standard diet plan and the standard exercise plan, and reduces the user's response to the standard diet plan. And the difficulty of completing the standard exercise program improves the user experience.

Hereinafter, the steps included in the method for generating a user portrait according to an exemplary embodiment of the present disclosure will be explained and described in detail with reference to the accompanying drawings.

First, the terms involved in the exemplary implementation examples of the present disclosure are explained and described.

Health file: A wide table that records the patient's personal basic information, disease/treatment information, and life information.

Guidelines: Through the nutrition/exercise guidelines, the calculated personal standard consumption and intake, as well as the standard exercise time, exercise intensity and other indicators.

Operational research optimization: The optimization process of finding feasible solutions within a given boundary range and finding the best solution from the feasible solutions.

Positive feedback: It means that the controlled part sends out feedback information, and its direction is consistent with the control information, which can promote or strengthen the activities of the control part; it can make the process continue to strengthen until the final physiological function is completed.

Personalized recommendation: Provide different information combinations for different users.

Recommendation recall: Select the part related to the current recommendation by the user (according to user information, user preference, historical behavior and other information) from the global candidate library as the candidate set.

Recommended sorting: Score the recall results of multiple channels uniformly, and sort according to the size of the scores.

Next, the purpose of the invention of the exemplary embodiments of the present disclosure is explained and illustrated. Specifically, the present disclosure improves the calculation of the content of the three major nutrients (protein, fat and carbohydrate), the calorie intake, the proportion of three meals, the proportion of trace elements, the duration of exercise, and the frequency of exercise. Under the sugar target, reduce the difficulty of completing the target. Through punch cards, user logs and other recording tools, improve the system and user information exchange, and further improve user satisfaction with recommendations.

Hereinafter, steps S110 to S140 will be explained and described.

In step S110, the disease information and daily life information of the target user are acquired, and according to the disease information and the daily life information, user tags of the target user in multiple different dimensions are determined.

In this exemplary embodiment, first, the health file of the target user (patient) can be obtained, and the health file can be used to store user information, and then the target user's disease information and daily life information including disease information and daily life information are extracted from the health file; wherein , the disease information may include basic patient information, physical information, diabetes information, hypertension information, hyperlipidemia information, hyperuric acid information, complications information, hormone information, etc.; daily life information may include diet information, sleep information, anxiety information, depression information Information, physical activity information, and cardiopulmonary function information; wherein, the data of the health record comes from questionnaires.

Further, user tags of the target user in multiple different dimensions may be determined according to the disease information and daily behavior information. Specifically, it may include: first, according to the disease symptom information and physical information of the target user in the disease information, determine the first user label of the target user in the dimension of weight management; secondly, according to the daily life information, determine The target user has a second user label on the dimension of eating activity, a third user label on the physical activity dimension, and a fourth user label on the emotional activity dimension.

Wherein, calculating the target user's second user label on the dimension of dietary activity, the third user label on physical activity, and the fourth user label on the emotional activity dimension of the target user according to the daily life information may further include: a In one aspect, the second user tag is calculated according to the diet information in the daily life information; on the other hand, the third user tag is calculated according to the physical activity information and cardiopulmonary function information in the daily life information; In one aspect, the fourth user tag is calculated according to sleep information, anxiety information and depression information in the daily life information.

In detail, the above-mentioned user tags may include a weight management tag (the first user tag in the weight management dimension), a diet activity tag (the second user tag in the diet activity dimension), and a physical activity tag (the third user tag in the physical activity dimension) User label), anxiety and depression label (the fourth user label on the emotional activity dimension) four categories. in:

The dietary activity label may include dietary habits and dietary risks; among them, the factors affecting dietary habits may include: dietary scene preference, staple food preference, and cooking method preference, and of course dairy product preference and snack intake preference, etc. No special restrictions are made. Factors affecting dietary risk may include risk of liver and kidney function, glycemic index of recommended foods, and dietary taboos. At the same time, the staple food preference can also be divided into staple food intake grading, protein intake grading, oil intake grading, and fruit intake grading.

The factors affecting the physical activity label can include physical activity classification and cardiopulmonary function classification, etc.; the factors affecting the weight management label can include resting metabolic rate, daily calorie consumption, and exercise time; the factors affecting the anxiety and depression label can include anxiety level and sleep. quality level, etc.

It should be supplemented here that the above-mentioned user tags may also include tags of other dimensions, such as user tags of the dimension of genetic medical history, etc., which is not limited in this example. Of course, the specific factors included in each user label can also be adjusted according to actual needs. Meanwhile, the value range of the user tag can be divided into three categories, namely, multi-value character type, single-value character type, and single-value floating-point type.

Hereinafter, taking the resting metabolic rate as an example, the specific calculation method of each user tag will be described as an example. For example, the resting metabolic rate of the target user can be calculated according to the user's gender, age, height and weight, as shown in FIG. 2 for details. For example: if the gender is male, the resting metabolic rate can be calculated by the following formula (1):

Resting metabolic rate = 9.99*(weight-105)+6.25*height-4.92*age+5; formula (1)

If the gender is female, the resting metabolic rate can be calculated by the following formula (2):

Resting metabolic rate = 9.99*(weight-105)+6.25*height-4.92*age-161; formula (2)

If a man is 175cm tall, weighs 80kg, and is 43 years old, his resting metabolic rate is: 636.94;

The calculation method of daily calorie consumption is: resting metabolic rate * metabolic coefficient.

It needs to be further explained here that the calculation methods of user labels of other dimensions are shown in Table 1 and Table 2 in the appendix below, and this example does not impose special restrictions on this.

In step S120, according to the user tags on each of the different dimensions and the daily behavior information of the target user, the current exercise schedule and the current diet schedule of the target user are calculated.

In this exemplary embodiment, referring to FIG. 3 , according to the user labels on each of the different dimensions and the daily behavior information of the target user, the current exercise plan and the current diet plan of the target user are determined, and the current exercise plan and the current diet plan can be determined. It includes steps S310-S330.

In step S310, the user plan information of the target user is calculated according to the user labels on each of the different dimensions and the daily behavior information of the target user; wherein the user plan information includes the user's planned heart rate, the user's planned exercise A variety of the duration, the user's planned exercise intensity, the user's planned total energy intake, and the user's planned intake of protein, fat, and carbohydrate in the total energy.

In step S320, the user plan information is adjusted according to the user's actual information in the target user's daily behavior information; wherein the user's actual information includes the user's actual heart rate, the user's actual exercise duration, the user's actual exercise intensity, The total energy actually consumed by the user and the ratios of protein, fat and carbohydrates actually consumed by the user in the total energy.

In step S330, the current exercise schedule is generated according to the adjusted user's planned heart rate, the user's planned exercise duration, and the user's planned exercise intensity, and the adjusted total energy and the user's planned intake of protein are , the proportion of fat and carbohydrates in the total energy, and generate the current diet plan.

Hereinafter, steps S310 to S330 will be explained and described. Specifically, the user policy is an index that actually guides the user's calorie consumption, intake, and the ratio of three meals, and is mainly numerical. The user policy may include exercise policy and diet policy, ie the current exercise schedule and current diet schedule as described herein. Among them, the exercise policy (current exercise plan) may include indicators such as the user's planned heart rate, exercise duration, and exercise intensity; the diet policy (current diet plan) may include total energy, protein percentage range, fat percentage range, carbohydrate percentage The ratio range, the proportion of breakfast/lunch/dinner/snack, and the range of trace elements, etc.

Further, in the calculation process of the current exercise plan and the current diet plan, the input terminal may include the user labels of the above-mentioned different dimensions and the daily behavior information (records) and behavior records of the target user. For example, the generation of the user's planned heart rate may refer to FIG. 4 . In Figure 4, the user's planned heart rate (planned average heart rate) can be obtained through the exercise intensity label, the resting heart rate label and the reserve heart rate label. The specific calculation method can be shown in the following formula (3):

Planned heart rate = (0.4 + exercise intensity * 0.1) * reserve heart rate + resting heart rate; formula (3)

Among them, reserve heart rate = maximum heart rate - resting heart rate;

Maximum heart rate = 220 - age.

It should be supplemented here that the calculation methods of other planning information are similar to the conventional calculation methods in the art, and will not be repeated here.

Further, after the user plan information is obtained, the user plan information can be adjusted according to the actual information of the user, thereby generating a current exercise plan table and a current diet plan table. Among them, in the specific adjustment process, if the calculation result of the accumulated value of the user's exercise check-in and stay time on the exercise plan page does not reach the minimum threshold, the user's daily energy intake value will be reduced, and then other plan information will be adjusted. Adjustment.

In step S130, a target plan table is constructed according to the current exercise plan table and the current diet plan table, and a user portrait of the target user is generated according to the target plan table, preset sports category and food category.

In this exemplary embodiment, referring to FIG. 5 , a target plan is constructed according to the current exercise plan and the current diet plan, and the target plan is generated according to the goal plan and preset sports categories and food categories. The user portrait of the target user may include steps S510-S530.

In step S510, a first objective function is generated according to the adjusted user's planned heart rate, the user's planned exercise time, and the user's planned exercise intensity in the current exercise schedule.

In step S520, a second target is generated according to the adjusted total energy planned by the user and the proportion of protein, fat and carbohydrates planned by the user in the total energy in the current diet plan table function.

In step S530, using the current exercise schedule as the first boundary condition of the first objective function, and using the current diet schedule as the second boundary condition of the second objective function, according to the preset The first objective function and the second objective function are solved according to the sports category and the food category, and the user portrait of the target user is obtained; wherein, the user portrait includes the diet plan and the exercise plan of the target user.

Hereinafter, steps S510 to S530 will be explained and described. Specifically, in the process of generating user portraits (recommendation of diet and exercise plan), you can use the operation research optimization method to calculate the user's feasible recall results according to the diet policy, exercise policy, and the materials to be recommended (sports category and food category), which can be generated. User portrait. Among them, the operational research optimization algorithm uses the target data to construct the objective function and boundary conditions, and uses the material data as the solution space to solve the feasible and optimal solutions in the solution space.

For example, the objective function can be:

Calories=a*carbs+b*protein+c*fat;

Carbohydrates=x11*breakfast+x12*lunch+x13*dinner+x14*snack;

Protein=x21*breakfast+x22*lunch+x23*dinner+x24*snack;

Fat = x31*breakfast+x32*lunch+x33*dinner+x34*snack;

Boundary conditions:

a+b+c=1;

x11+x12+x13+x14=1;

x21+x22+x23+x24=1;

x31+x32+x33+x34=1;

x14<=0.2 and x14>=0;

x24<=0.2 and x24>=0;

x34<=0.2 and x34>=0.

Sports categories can include jogging, jogging, brisk walking, fast running, rope skipping and yoga, etc. Food categories can include rice, millet, brown rice, vegetables (spinach, cabbage, tomatoes, zucchini, broccoli, wax gourd, etc.), Steamed buns and meat (fish, chicken, duck, beef, etc.) can be adjusted according to the actual situation, which is not limited in this example.

Further, in order to improve the accuracy of the solution results and the solution efficiency, the user portrait generation method may further include: filtering the sports scenes and sports preferences in the sports category based on preset filtering rules, and filtering the food category. Foods are filtered in the glycemic index. For example, before the material data (sports category and food category) is input into the operation research optimization calculation model, it must first go through business filtering. scene and sports preferences, etc.

In step S140, a standard diet plan and a standard exercise plan are matched for the target user according to the user portrait, and the standard diet plan and standard exercise plan are sent to the terminal device where the target user is located.

In this exemplary embodiment, first, matching a standard diet plan and a standard exercise plan for the target user according to the user portrait, which may specifically include: matching the user portrait to the user's exercise preference according to the user's exercise preference in the daily behavior information. The diet plan and the exercise plan are sorted, and the standard diet plan and the standard exercise plan are obtained according to the sorting result. Specifically, the feasible solutions and optimal solutions calculated by the operation research optimization can be input into the sorting module. In the sorting module, the actual user preferences and actual user behaviors of the target users are used for sorting, and the sorted TOP3 results are recalled as The standard diet plan and the standard exercise plan are sent to the terminal device where the target user is located, so that the user can view the standard diet plan and the standard exercise plan.

Hereinafter, the method for generating a user portrait according to an exemplary embodiment of the present disclosure will be further explained and described with reference to FIG. 6 . Referring to Figure 6, the user portrait generation method may include the following steps:

Step S610, collect the health profile data of the target user, and calculate the user label;

Step S620, formulate a user policy according to the user tag;

Step S630, filter the material data, and perform operational research optimization according to the filtered material data and the user policy to obtain multiple feasible solutions and an optimal solution;

Step S640 , sort the feasible solutions and the optimal solutions according to the user behavior of the target user, and then obtain the final recommendation scheme, and adjust the user label and the recommendation scheme according to the specific feedback information of the target on the recommendation scheme.

The user portrait generation method provided by the present disclosure solves the problem that it is difficult to form positive feedback without user feedback as a label in the recommendation of diabetes diet and exercise in the prior art; The diversity and accuracy of the scheme are increased; finally, the recommendation of diet and exercise using end-to-end neural networks in the existing technology is avoided, and the problem that health managers are difficult to interpret the recommendation results in real application scenarios is not considered .

The present disclosure also provides a user portrait generation device. Referring to FIG. 7 , the user portrait generation device may include a user label calculation module 710 , a schedule generation module 720 , a user portrait generation module 730 and a scheme matching module 740 . in:

The user tag calculation module 710 can be used to obtain disease information and daily life information of the target user, and determine user tags of the target user in multiple different dimensions according to the disease information and daily life information;

The plan calculation module 720 may be configured to determine the current exercise plan and the current diet plan of the target user according to the user tags on each of the different dimensions and the daily behavior information of the target user;

The user portrait generation module 730 can be used to construct a target plan according to the current exercise plan and the current diet plan, and generate the user portrait of the target user according to the goal plan, the preset sports category and the food category. ;

The plan matching module 740 may be configured to match a standard diet plan and a standard exercise plan for the target user according to the user portrait, and send the standard diet plan and standard exercise plan to the terminal device where the target user is located.

In an exemplary embodiment of the present disclosure, according to the disease information and daily behavior information, user tags of the target user in multiple different dimensions are determined, including:

According to the disease symptom information and physique information of the target user in the disease information, determine the first user label of the target user in the dimension of weight management;

According to the daily life information, the target user's second user label on the dimension of eating activity, the third user label on the physical activity, and the fourth user label on the emotional activity dimension are determined.

In an exemplary embodiment of the present disclosure, according to the daily life information, a second user label on the eating activity dimension, a third user label on the physical activity, and an emotional activity dimension of the target user are determined The fourth user tab of , including:

Calculate the second user tag according to the diet information in the daily life information;

Calculate the third user tag according to the physical activity information and the cardiopulmonary function information in the daily life information;

The fourth user tag is calculated according to sleep information, anxiety information and depression information in the daily life information.

In an exemplary embodiment of the present disclosure, determining the current exercise plan and the current diet plan of the target user according to the user tags on each of the different dimensions and the daily behavior information of the target user, including:

Calculate the user plan information of the target user according to the user labels on each of the different dimensions and the daily behavior information of the target user; wherein the user plan information includes the user's planned heart rate, the user's planned exercise duration, and the user's planned exercise. a variety of the intensity, the total energy the user plans to consume, and the proportion of protein, fat, and carbohydrates the user plans to consume in the total energy;

The user plan information is adjusted according to the user's actual information in the target user's daily behavior information; wherein the user's actual information includes the user's actual heart rate, the user's actual exercise duration, the user's actual exercise intensity, and the user's actual intake. The total energy and a variety of the proportions of protein, fat and carbohydrates actually consumed by the user in the total energy;

According to the adjusted user's planned heart rate, the user's planned exercise duration, and the user's planned exercise intensity, the current exercise schedule is generated, and based on the adjusted total energy planned by the user and the planned intake of protein, fat and carbohydrates by the user In the proportion of the total energy, the current diet plan table is generated.

In an exemplary embodiment of the present disclosure, a goal plan is constructed according to the current exercise plan and the current diet plan, and the goal is generated according to the goal plan, a preset sports category and a food category User profile, including:

generating a first objective function according to the adjusted user's planned heart rate, the user's planned exercise time, and the user's planned exercise intensity in the current exercise schedule;

generating a second objective function according to the adjusted total energy planned by the user and the proportion of protein, fat and carbohydrates planned by the user in the total energy in the current diet plan table;

Taking the current exercise schedule as the first boundary condition of the first objective function, and using the current diet schedule as the second boundary condition of the second objective function, according to the preset sports category and food The category solves the first objective function and the second objective function to obtain a user portrait of the target user; wherein the user portrait includes the target user's diet plan and exercise plan.

In an exemplary embodiment of the present disclosure, the user portrait generating apparatus further includes:

The data filtering module is configured to filter the sports scenes and sports preferences in the sports category based on preset filtering rules, and filter the blood sugar generation index of the food in the food category.

In an exemplary embodiment of the present disclosure, matching a standard diet plan and a standard exercise plan for the target user according to the user portrait includes:

Sort the diet plan and exercise plan in the user portrait according to the user's exercise preference in the daily behavior information, and obtain the standard diet plan and standard exercise plan according to the sorting result.

The specific details of each module in the above-mentioned user portrait generation device have been described in detail in the corresponding user portrait generation method, and thus are not repeated here.

It should be noted that although several modules or units of the apparatus for action performance are mentioned in the above detailed description, this division is not mandatory. Indeed, according to embodiments of the present invention, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one module or unit described above may be further divided into multiple modules or units to be embodied.

Additionally, although the various steps of the methods of the present invention are depicted in the figures in a particular order, this does not require or imply that the steps must be performed in that particular order, or that all illustrated steps must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, and the like.

In an exemplary embodiment of the present invention, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention can be embodied in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, which may be collectively referred to herein as implementations "circuit", "module" or "system".

An electronic device 800 according to this embodiment of the present invention is described below with reference to FIG. 8 . The electronic device 800 shown in FIG. 8 is only an example, and should not impose any limitation on the function and scope of use of the embodiments of the present invention.

As shown in FIG. 8, electronic device 800 takes the form of a general-purpose computing device. Components of the electronic device 800 may include, but are not limited to, the above-mentioned at least one processing unit 810 , the above-mentioned at least one storage unit 820 , a bus 830 connecting different system components (including the storage unit 820 and the processing unit 810 ), and a display unit 840 .

Wherein, the storage unit stores program codes, and the program codes can be executed by the processing unit 810, so that the processing unit 810 executes various exemplary methods according to the present invention described in the above-mentioned “Exemplary Methods” section of this specification Implementation steps. For example, the processing unit 810 may perform step S110 as shown in FIG. 1 : acquire disease information and daily life information of the target user, and determine, according to the disease information and daily life information, that the target user is in multiple different the user label on the dimension; Step S120: According to the user label on each of the different dimensions and the daily behavior information of the target user, determine the current exercise plan and the current diet plan of the target user; Step S130: According to the The current exercise plan and the current diet plan are constructed to construct a target plan, and according to the target plan, the preset sports category and the food category, the user portrait of the target user is generated; Step S140: According to the user portrait, The target user matches the standard diet plan and the standard exercise plan, and sends the standard diet plan and the standard exercise plan to the terminal device where the target user is located.

The storage unit 820 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 8201 and/or a cache storage unit 8202 , and may further include a read only storage unit (ROM) 8203 .

The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, An implementation of a network environment may be included in each or some combination of these examples.

The bus 830 may be representative of one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local area using any of a variety of bus structures bus.

The electronic device 800 may also communicate with one or more external devices 900 (eg, keyboards, pointing devices, Bluetooth devices, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with Any device (eg, router, modem, etc.) that enables the electronic device 800 to communicate with one or more other computing devices. Such communication may take place through input/output (I/O) interface 850 . Also, the electronic device 800 may communicate with one or more networks (eg, a local area network (LAN), a wide area network (WAN), and/or a public network such as the Internet) through a network adapter 860 . As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830 . It should be understood that, although not shown, other hardware and/or software modules may be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives and data backup storage systems.

From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein may be implemented by software, or may be implemented by software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of software products, and the software products can be stored in a non-volatile storage medium (which can be CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to cause a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to an embodiment of the present invention.

In an exemplary embodiment of the present invention, there is also provided a computer-readable storage medium on which a program product capable of implementing the above-mentioned method of the present specification is stored. In some possible implementations, aspects of the present invention can also be implemented in the form of a program product comprising program code for enabling the program product to run on a terminal device The terminal device performs the steps according to various exemplary embodiments of the present invention described in the "Example Method" section above in this specification.

A program product for implementing the above method according to an embodiment of the present invention may adopt a portable compact disc read only memory (CD-ROM) and include program codes, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples (non-exhaustive list) of readable storage media include: electrical connections with one or more wires, portable disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal in baseband or as part of a carrier wave with readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable signal medium can also be any readable medium, other than a readable storage medium, that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural Programming Language - such as the "C" language or similar programming language. The program code may execute entirely on the user computing device, partly on the user device, as a stand-alone software package, partly on the user computing device and partly on a remote computing device, or entirely on the remote computing device or server execute on. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (eg, using an Internet service provider business via an Internet connection).

Furthermore, the above-mentioned figures are merely schematic illustrations of the processes included in the methods according to the exemplary embodiments of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the chronological order of these processes. In addition, it is also readily understood that these processes may be performed, for example, synchronously or asynchronously in multiple modules.

Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the invention which follow the general principles of the invention and which include common knowledge or conventional techniques in the art to which the invention is not invented . The specification and examples are to be regarded as exemplary only, with the true scope and spirit of the invention being indicated by the claims.

Table 1

Table 2

Claims

A method for generating user portraits, comprising:

Acquiring disease information and daily life information of the target user, and determining user labels of the target user in multiple different dimensions according to the disease information and daily life information;

Determine the current exercise plan and the current diet plan of the target user according to the user tags on each of the different dimensions and the daily behavior information of the target user;

Build a target plan according to the current exercise plan and the current diet plan, and generate a user portrait of the target user according to the goal plan, preset sports categories and food categories;

Match a standard diet plan and a standard exercise plan for the target user according to the user portrait, and send the standard diet plan and standard exercise plan to the terminal device where the target user is located.
The method for generating a user portrait according to claim 1, wherein, according to the disease information and daily behavior information, determining the user labels of the target user in multiple different dimensions, comprising:

According to the disease symptom information and physique information of the target user in the disease information, determine the first user label of the target user in the dimension of weight management;

According to the daily life information, the target user's second user label on the dimension of eating activity, the third user label on the physical activity, and the fourth user label on the emotional activity dimension are determined.
The method for generating user portraits according to claim 2, wherein, according to the daily life information, the second user label of the target user in the dimension of eating activity, the third user label of physical activity, and the emotional activity of the target user are determined. The fourth user label in the dimension, including:

Calculate the second user tag according to the diet information in the daily life information;

Calculate the third user tag according to the physical activity information and cardiopulmonary function information in the daily life information;

The fourth user tag is calculated according to sleep information, anxiety information and depression information in the daily life information.
The method for generating a user portrait according to claim 1, wherein the current exercise plan and the current diet plan of the target user are determined according to the user labels on each of the different dimensions and the daily behavior information of the target user, include:

Calculate the user plan information of the target user according to the user labels on each of the different dimensions and the daily behavior information of the target user; wherein the user plan information includes the user's planned heart rate, the user's planned exercise duration, and the user's planned exercise. a variety of the intensity, the total energy the user plans to consume, and the proportion of protein, fat, and carbohydrates the user plans to consume in the total energy;

The user plan information is adjusted according to the user's actual information in the target user's daily behavior information; wherein the user's actual information includes the user's actual heart rate, the user's actual exercise duration, the user's actual exercise intensity, and the user's actual intake. The total energy and a variety of the proportions of protein, fat and carbohydrates actually consumed by the user in the total energy;

According to the adjusted user's planned heart rate, the user's planned exercise duration, and the user's planned exercise intensity, the current exercise schedule is generated, and based on the adjusted total energy planned by the user and the planned intake of protein, fat and carbohydrates by the user In the proportion of the total energy, the current diet plan table is generated.
The method for generating a user portrait according to claim 1, wherein a target plan is constructed according to the current exercise plan and the current diet plan, and the target plan is generated according to the goal plan, a preset sports category and a food category. Describe the user profile of the target user, including:

generating a first objective function according to the adjusted user's planned heart rate, the user's planned exercise time, and the user's planned exercise intensity in the current exercise schedule;

generating a second objective function according to the adjusted total energy planned by the user and the proportion of protein, fat and carbohydrates planned by the user in the total energy in the current diet plan table;

Taking the current exercise schedule as the first boundary condition of the first objective function, and using the current diet schedule as the second boundary condition of the second objective function, according to the preset sports category and food Category, solve the first objective function and the second objective function to obtain the user portrait of the target user;

Wherein, the user portrait includes the target user's diet plan and exercise plan.
The user portrait generation method according to claim 5, wherein before the first objective function and the second objective function are solved according to the preset sports category and food category, the user portrait generation method further include:

The sports scenes and sports preferences in the sports category are filtered based on preset filtering rules, and the blood sugar generation index of the food in the food category is filtered.
The method for generating a user portrait according to claim 1, wherein matching a standard diet plan and a standard exercise plan for the target user according to the user portrait, comprising:

Sort the diet plan and exercise plan in the user portrait according to the user's exercise preference in the daily behavior information, and obtain the standard diet plan and standard exercise plan according to the sorting result.
A user portrait generation device, comprising:

a user label calculation module, used to obtain disease information and daily life information of a target user, and determine user labels of the target user in multiple different dimensions according to the disease information and daily life information;

a plan table calculation module, configured to determine the current exercise plan table and the current diet plan table of the target user according to the user labels on each of the different dimensions and the daily behavior information of the target user;

a user portrait generation module, configured to construct a target plan according to the current exercise plan and the current diet plan, and generate a user portrait of the target user according to the goal plan, preset sports categories and food categories;

A plan matching module, configured to match a standard diet plan and a standard exercise plan for the target user according to the user portrait, and send the standard diet plan and the standard exercise plan to the terminal device where the target user is located.
A computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the method for generating a user portrait according to any one of claims 1-7.
An electronic device comprising:

processor; and

a memory for storing executable instructions for the processor;

Wherein, the processor is configured to execute the method for generating a user portrait according to any one of claims 1-7 by executing the executable instructions.