WO2022237526A1

WO2022237526A1 - User behavior feedback method and system based on energy state change

Info

Publication number: WO2022237526A1
Application number: PCT/CN2022/089277
Authority: WO
Inventors: 林雷
Original assignee: 林雷
Priority date: 2021-05-13
Filing date: 2022-04-26
Publication date: 2022-11-17
Also published as: CN113241149A

Abstract

Disclosed in the present disclosure are a user behavior feedback method and system based on an energy state change. The method comprises: acquiring at least two impedance values and at least two body parameters of the body of a user which are measured within a predetermined period, wherein the body parameters are physiological parameters of the user; determining an energy state change in the user at least according to the at least two impedance values and the at least two body parameters; and determining, according to predetermined information, a behavior characteristic corresponding to the user, and feeding same back to the user, wherein the behavior characteristic is a behavior characteristic that causes the energy state change in the user, and the predetermined information at least comprises the energy state change in the user. By means of the present disclosure, problems in the prior art caused by manually supervising weight loss are solved, thereby achieving the effect of scientific supervision, and being conducive to the improvement of the physical health of people.

Description

A user behavior feedback method and system based on energy state changes

Cross References to Related Applications

This disclosure claims the priority of the Chinese patent application CN202110522959.1 entitled "A User Behavior Feedback Method and System Based on Energy State Change" filed on May 13, 2021, the entire content of which is incorporated by reference into this disclosure .

technical field

The present disclosure relates to the field of software, in particular, to a user behavior feedback method and system based on energy state changes.

Background technique

Obesity has become a public health problem, and the medical profession has long proven that lifestyle management is the only positive way to lose weight. But when people think of lifestyle management, people’s first reaction is to maintain hunger, exercise a lot, and have difficulty persisting in the face of temptation and other negative emotions, so not many people choose.

Users who need to lose weight generally hope to get more professional guidance and supervision, so that they can persist for a long time.

Some professional weight loss institutions can provide humanized and personalized help for customers to change their lifestyles through a large number of professional services, but such services are expensive and not available to everyone.

Moreover, this method relies on the specialization of service personnel, and has relatively high requirements for service personnel.

Contents of the invention

Embodiments of the present disclosure provide a user behavior feedback method and system based on energy state changes, so as to at least solve problems caused by manual supervision of weight loss in the prior art.

According to one aspect of the present disclosure, there is provided a user behavior feedback method based on energy state changes, including: acquiring at least two impedance values and at least two body parameters of the user's body measured within a predetermined period, wherein the body The parameter is a physiological parameter of the user; at least according to the at least two impedance values and the at least two physical parameters, the energy state change of the user is determined, wherein the energy state change is used to indicate at least one of the following: Energy intake, energy intake structure, energy consumption, energy consumption mode; determine the corresponding behavioral characteristics of the user according to predetermined information, and give feedback to the user, wherein the behavioral characteristics cause the energy state of the user A changed behavior feature, wherein the predetermined information includes at least a change in the energy state of the user.

According to another aspect of the present disclosure, there is also provided an electronic device, including: a screen; for displaying at least one of the following obtained from the above measurement: body parameters, impedance values, and behavioral characteristics; software, for executing the above method; The memory is used to store the software; the processor is used to run the software.

According to another aspect of the present disclosure, there is also provided a user behavior feedback system based on energy state changes, including: an acquisition module, configured to acquire at least two impedance values and at least two impedance values of the user's body measured within a predetermined period A physical parameter, wherein the physical parameter is a physiological parameter of the user; a determination module, configured to determine the energy state change of the user at least according to the at least two impedance values and the at least two physical parameters, wherein, The energy status change is used to indicate at least one of the following: energy intake, energy intake structure, energy consumption, and energy consumption mode; the feedback module determines the corresponding behavior characteristics of the user according to predetermined information, and sends to the User feedback, wherein the behavior feature is a behavior feature that causes a change in the user's energy state, and the predetermined information includes: the change in the user's energy state.

In the embodiments of the present disclosure, at least two impedance values and at least two physical parameters of the user's body measured within a predetermined period are obtained, wherein the physical parameters are physiological parameters of the user; at least according to the At least two impedance values and the at least two body parameters determine a change in energy state of the user, wherein the change in energy state is used to indicate at least one of the following: energy intake, energy intake structure, energy expenditure . Energy consumption mode; determine the corresponding behavioral characteristics of the user according to predetermined information, and feed back to the user, wherein the behavioral characteristics are behavioral characteristics that cause changes in the energy state of the user, wherein the predetermined information includes at least The user's energy state changes. The disclosure solves the problems caused by relying on manual supervision on weight loss in the prior art, achieves the effect of scientific supervision, and is beneficial to improving people's health.

Description of drawings

The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure, and the schematic embodiments and descriptions of the present disclosure are used to explain the present disclosure, and do not constitute improper limitations to the present disclosure. In the attached picture:

Fig. 1 is a flowchart of a user behavior feedback method based on energy state changes according to an embodiment of the present disclosure.

Detailed ways

It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

It should be noted that the steps shown in the flowcharts of the accompanying drawings may be performed in a computer system, such as a set of computer-executable instructions, and that although a logical order is shown in the flowcharts, in some cases, The steps shown or described may be performed in an order different than here.

The reason why a healthy lifestyle is easy to know and difficult to practice is that people usually only pay attention to timely feedback and take action, but the impact of unhealthy lifestyle on health has a great lag and subtle effect, so people are concerned about some of the lifestyle Bad habits are not given enough attention; at the same time, because everyone's age, gender, genes, and living environment are different, the same lifestyle affects everyone in different degrees, so although many people know the general principles of healthy living, But when it comes to the details of your own life, there is often no specific method, which makes it impossible for everyone to start. In this embodiment, a method is provided that can be scaled up and at low cost so that ordinary people can easily, naturally and effortlessly adjust their lifestyles and gain health.

This embodiment provides a user behavior feedback method based on energy state changes. FIG. 1 is a flowchart of a user behavior feedback method based on energy state changes according to an embodiment of the disclosure. As shown in FIG. 1 , the process includes the following step:

Step S102, acquiring at least two resistance values and at least two physical parameters of the user's body measured within a predetermined period, wherein the physical parameters are physiological parameters of the user;

Step S104, determining the energy state change of the user at least according to at least two resistance values and at least two body parameters, wherein the energy state change is used to indicate at least one of the following: energy intake, energy intake structure, energy Consumption, energy consumption pattern;

The resistance value is used in the above steps. This is because the different states of each person’s body correspond to different resistance values. The user’s physical state can be determined by the resistance value. In order to ensure a more accurate determination of the energy state, you can also increase A physical parameter, which may include but not limited to at least one of the following: weight, age, gender, and height information. As an optional manner, the above-mentioned resistance value is an impedance value of a human body. More preferably, it can be further said, the impedance value of the body below the waist and abdomen (including) or the change of the body impedance value.

In the above steps, the energy state can be obtained according to the physiological parameters and the resistance value, and then the changes among the multiple energy states can be obtained according to the multiple energy states.

In one embodiment, collected user data (for example, data stored in a medical institution that has obtained user authorization) can be used as training data, and each set of training data includes a user's height , body weight and other physiological parameters, a resistance value, and a fat parameter corresponding to the physiological parameter and the resistance value, and the fat parameter is used to indicate the user's fat content (for example, body fat percentage and/or muscle mass). When the amount of training data exceeds the threshold, the training data can be sent to the machine learning engine for training.

The machine learning engine can use an existing machine learning engine, and the specific engine construction and operation process can refer to the technical manuals of each engine. Those skilled in the art can build corresponding machine learning engines according to these technical manuals. After the machine learning engine is trained using multiple sets of training data, a first machine learning model can be obtained. After obtaining the model, the model can be used to obtain the user's fat parameters. As long as the user's physiological parameters and resistance values are input into the first model, the first model can output the corresponding fat parameters.

Then the user's energy state is obtained according to the fat parameter and the above-mentioned physiological parameters. In the above example, the fat parameter is used, which can also be regarded as a kind of physiological parameter. If the user directly inputs the fat parameter, the energy status can be obtained according to the following example.

As another implementation, since the machine learning engine has been adopted, the machine learning engine can also be used to train a second model, and each set of training data in the multiple sets of training data used to train the model includes the user's fat parameters and physiological parameters, and the energy state corresponding to the fat parameters and physiological parameters. After the second model is obtained through training, the corresponding energy state can be obtained only by inputting fat parameters and physiological parameters.

The obtained energy status can also be displayed to the user, so that the user can perceive it himself. If there is no need to display the energy status to the user, the third model can be used, and each set of training data used to train the model includes the user's fat parameters and physiological parameters, and the behavior corresponding to the fat parameters and physiological parameters Suggest. The difference between the third model and the second model is that the direct output of the model is the behavior suggestion. After the second model is obtained through training, as long as fat parameters and physiological parameters are input, corresponding behavior suggestions can be obtained.

After obtaining the energy state, the change of the energy state can be obtained according to at least two energy states.

Step S106, determining the corresponding behavioral characteristics of the user according to predetermined information, and feeding back to the user, wherein the behavioral characteristics are behavioral characteristics that cause changes in the energy state of the user; wherein the predetermined information includes at least: changes in the energy state of the user. In an implementation manner, the predetermined information may further include: physiological parameters and/or resistance values.

The model based on the machine learning engine in the above embodiments is used after accumulating a large amount of training data. If the amount of training data is not enough, the pre-configured correspondence can be used. For example, the pre-configured resistance value, Correspondence between body parameters and energy state to obtain energy state. These corresponding relationships may be obtained by measuring in advance by accurate measurement means. Alternatively, various measured data can also be fitted into a function by software, and the energy state output by the function can be obtained by taking the resistance value and body parameters as the input of the function.

As for the determination of the behavior characteristic, it may also be determined according to the relationship between the pre-configured predetermined information and the behavior characteristic. The relationship between these pre-configured predetermined information and behavior characteristics is obtained through statistics on samples. When the number of samples reaches the level where machine learning training can be performed, a machine learning model can be trained to obtain behavioral features based on predetermined information, which can be called a behavioral feature model. The behavior feature model is obtained through training using multiple sets of training data, each set of training data includes predetermined information and a label, and the label is used to identify the behavior feature under the predetermined information. After training, a convergent behavioral feature model is obtained, which can be used after verification data verification, and the verification data also comes from sample data. The predetermined information in step S106 is input into the behavior characteristic model, and the behavior characteristic model can input a label for indicating the behavior characteristic.

No matter what implementation method is used, in the above steps, as long as a user's ability to handle energy (or heat) is determined through the cooperation of the resistance value and body parameters, behavior suggestions can be provided to the user through the measurement of each cycle. The processing capability can also be understood as including how many calories the user has consumed and how many calories have been consumed. The above behavioral characteristic model can directly obtain the behavioral characteristics. For the change of the energy state, the change of the energy state can be determined by comparison after the energy state is obtained. It has been explained above, and will not be repeated here.

In this embodiment, it can also be processed by a classification method. For example, at least one of the following can be sorted and classified: the direction and/or magnitude of body impedance change at a predetermined time, the direction and/or magnitude of body parameter change, and the classification based on It is each combination of changes that corresponds to a specific behavioral characteristic that caused the change. For example, caloric intake exceeds a predetermined standard value, which corresponds to a combination of multiple sets of impedance changes and/or body parameter changes. Therefore, by measuring changes in body impedance and body parameters at a predetermined time, the behavioral characteristics of the user's current lifestyle can be deduced in reverse.

There may also be many kinds of classification methods, for example, classification may be performed by means of machine learning.

The model trained by the machine learning can be called a classification model, and the classification model is obtained through multiple sets of training data training, each set of training data includes specific behavioral characteristics, and the body impedance and/or body parameters caused by the behavioral characteristics Variety. Taking specific behavioral characteristics as input, and taking changes in body impedance and/or body parameters as output, the trained model can be used to determine changes in body impedance and/or body parameters according to behavioral characteristics; With changes as input and specific behavioral features as output, the trained model can be used to output behavioral features based on changes in body impedance and/or body parameters.

When classifying, the correspondence with behavioral characteristics can be further classified and corresponded according to gender, age, height, living environment, etc.

As another way, body composition changes can be deduced through body impedance changes combined with body parameter changes, and then behavioral characteristics in lifestyle can be deduced through body composition changes; this derivation method can also be understood as a classification method, which is different from The difference in the above embodiment is that two classifications are performed. The specific manner adopted is the same as that of the foregoing embodiment, and will not be repeated here. The body composition here can include at least one of the following: body fat percentage, muscle mass, skeletal muscle percentage, internal fat, BMI, body water, protein, and bone mass; variables in body parameters can include blood pressure, blood sugar in addition to body weight etc. Other parameters will not be listed here one by one.

The above steps can be run in a program, and the program can be an application installed on a mobile device, or a software installed on a personal computer, or a service running on a server. In the following embodiments, software, applications, and services are all referred to as software. Using the software to make judgments and push behavioral suggestions can achieve large-scale applications without being limited by the number and capabilities of professional service personnel. In addition, for users, on the one hand, it is very easy to get behavior suggestions, and on the other hand, the software is based on objective physical values to get behavior suggestions, which is more scientific. Therefore, through the above steps, the problems caused by relying on manual supervision of weight loss in the prior art are solved, the effect of scientific supervision is achieved, and it is beneficial to improve people's health.

In an implementation manner, the aforementioned predetermined period may be in units of days, for example, the predetermined period may include at least two consecutive days. If the measurement is performed on a daily basis, at least two impedance values of the user's body and/or at least two a body parameter;. For example, measurements are taken at 7:00 am, 9:00 am and 11:00 pm every day. This measurement method can establish the relationship between time and resistance value and body parameters. However, this measurement is not a very accurate value, because the behavior of each user at different time points is different. In order to find a more reasonable measurement point in this embodiment, you can choose to get up every morning After defecation, in one embodiment, if multiple data in a day are needed, the following behaviors can also be measured: measure the resistance of the user's body after getting up every morning before defecating and before going to bed value and/or body parameters. If two impedance values and two body parameters are required, the two impedance values and the two body parameters.

As another implementation manner, when the user uses it for the first time, it may be based on obtaining two consecutive sets of body impedance values and/or at least two sets of body parameters of the user, and the sleeping time measured on the first day. The previous body impedance value and/or the body parameters of the user are obtained to obtain three sets of measurement results; at least according to the three sets of measurement results, the behavioral characteristics of the user on the first day are determined, wherein the behavioral characteristics are Behavioral features made by the user that affect the change in the energy state.

As another implementation manner, since the measurement is performed every day, the behavior of the user on that day may be determined according to the measurement results obtained from the daily measurement. For example, obtain the resistance value and/or at least one body parameter of the user's body measured on the day after getting up in the morning, after defecation in the morning, and before going to bed, and obtain three sets of measurement results; behavioral characteristics.

In one example, the user's physical state can be judged according to the fat difference and the muscle mass difference every other day. Specifically, when the fat difference of the next day is not a negative value and the difference of the muscle rate of the next day is not a positive value, it means that the user's body fat has not increased and the muscles have not decreased, so it is judged that the user's physical condition is normal; otherwise, it is judged that the user's physical condition is not normal , and then according to the resistance value, it is judged that the cause of the abnormal physical state of the user is excessive drinking water or lack of drinking water.

In order to get a more precise reason, it is also possible to determine the user's behavior on the day based on three sets of measurement results; receive feedback from the user on the real behavior of the day; determine the user's behavior on the day based on the user's first behavior and feedback on the day. For example, the user can be allowed to input the amount of drinking water, and further judgment can be made according to the amount of drinking water input by the user.

The behavior characteristics determined according to the changes in the user's energy state in the above example may be displayed to the user. The above-mentioned behavior characteristics may include at least one of the following: the amount of food eaten by the user; the eating structure of the user; the cooking method of the user eating; the quality of food eaten by the user; the eating behavior of the user; The status; the amount of activity of the user; the preference of the user's activity type; the degree of physical fatigue of the user; the analysis of the energy and substance metabolism of the user's body.

The above steps and/or functions will be described below in conjunction with a preferred implementation manner. Part or all of the above optional embodiments are combined in this preferred embodiment.

The behavior feedback software includes a measuring device that can measure body weight and body impedance at one time, and a data sending module that can send the measured body weight and body impedance values to the data processing module. The data processing module will give corresponding feedback information according to the user's measurements in different periods, different times, different states, and different contexts.

The physical state of the human body at any point in time is the result of all lifestyles accumulated in the past. Therefore, after the user's first measurement, the data analysis module deduces based on the user's weight, impedance, age, gender and height information. A summary of the characteristics of the user's past behavior is given as the first feedback to the user. Through this feedback, users are made aware of the direct correlation between their current physical state and lifestyle behaviors. Next, the software will give the user the best and second best weight, body fat and inner fat standard range according to the user's age and gender, and give the time required to reach each stage according to the general standard, giving the user hope , and lead him to promise himself.

Next, the software will give the user a practical plan based on the national standard dietary guidelines, allowing the user to adjust their diet to create a calorie gap based on their own understanding. At this time, the data collection module will count the user's daily wake-up (1) , the body weight (3) values after waking up in the morning (2) and before going to bed, and the average value and daily deviation value of the difference between each value are counted every day. Taking 3 to 7 days as the statistical cycle, and then give the user the second feedback point, that is, the overall state of the body's energy intake and consumption balance, specifically the user's intake capacity and consumption capacity, and the consumption capacity is divided into basic metabolic capacity, digestion Ability, Consumption Ability and Food Thermic Ability.

Combined with the analysis of the user's capabilities observed above, the system then gives user-customized plan suggestions. The system will have a manual coach interface, and the manual coach can choose from the above-mentioned plan suggestions that are easy for the user to implement and implement according to the content of the user's meal check-in. A method capable of achieving the calorie gap, given to the user and monitored for its implementation.

After the user starts to execute, the system will automatically locate the bad behaviors that affect the body that day according to the user's body weight and impedance measured three times a day, as well as the corresponding age, gender, height, etc., and give timely feedback through the interactive design of the system . So that users can be aware and make adjustments consciously.

The difference between this software and traditional BIA analysis is that this software is dedicated to studying the precise response of data changes to daily behavior and guiding users to consciously change behavior through appropriate feedback, rather than pursuing the accuracy of static body data.

The software in this preferred embodiment can accurately locate the user's behavior based on the body impedance and body weight data, and through a series of precise feedback point settings and subtle guidance, the user is encouraged to take conscious and spontaneous actions to change his behavior. Most importantly, for the user, all the feedback points can be unlocked by taking tens of seconds a day to measure body weight and body impedance. In order to achieve scale and low cost, more people can have lifestyle management with certain effects.

In this embodiment, an electronic device is also provided, including a memory and/or a processor, software is stored in the memory, and the processor is configured to run the software to execute the methods in the above embodiments. The electronic device may further include: a screen. The screen is used to display relevant information, for example, the screen is used to display the above-mentioned measured body parameters, resistance values, behaviors and/or behavior suggestions. If the screen is a touch screen, it can also be used as an input device through which various information can be input. Certainly, the electronic device may also include other types of input devices, for example, a physical or virtual keyboard, and for example, a microphone through which voice commands can be input.

The above-mentioned software may also be referred to as a computer program, which may also be loaded onto a computer or other programmable data processing device, so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, Therefore, the instructions executed on the computer or other programmable devices provide steps for realizing the functions specified in one or more processes of the flow chart and/or one or more blocks of the block diagram, and the corresponding and different steps can be through different modules. The software or program can also be referred to as a device or system.

In this embodiment, a user behavior feedback system based on energy state changes is also provided, including: a user behavior feedback system based on energy state changes, including: an acquisition module, configured to acquire At least two impedance values and at least two body parameters of the user's body, wherein the body parameters are physiological parameters of the user; a determination module configured to determine the energy state change of the user at least according to at least two impedance values and at least two body parameters, Wherein, the energy state change is used to indicate at least one of the following: energy intake, energy intake structure, energy consumption, energy consumption mode; the feedback module determines the corresponding behavior characteristics of the user according to predetermined information, and gives feedback to the user , wherein the behavior feature is a behavior feature that causes a change in the energy state of the user; wherein the predetermined information includes at least: a change in the energy state of the user. In an implementation manner, the predetermined information may further include: physiological parameters and/or resistance values.

The modules in the feedback system correspond to the steps in the above method, which have already been described in the method and will not be repeated here.

In one embodiment, the predetermined period is in units of days, the predetermined period includes at least two consecutive days, and the acquisition module is used to perform measurement at a fixed time point and/or a time point when a fixed behavior occurs in each day within the predetermined period Obtain at least two impedance values and/or at least two body parameters of the user's body; and/or, the acquisition module is used to obtain two adjacent impedance values and two body parameters within a predetermined period Two impedance values and two body parameters are measured after the same time period and the same fixed behavior; and/or, the acquisition module is also used to acquire two consecutive sets of body impedance values and/or at least two sets of body parameters of the user, and The body impedance value and/or body parameters of the user before going to bed measured on the first day, and three sets of measurement results are obtained; the feedback module is also used to determine the behavior characteristics of the user on the first day at least according to the three sets of measurement results, wherein, Behavior features are behavior features made by users that affect energy state changes.

In one embodiment, the fixed time point of each day for obtaining the impedance value and the body parameter/or the measurement point where the fixed behavior occurs is after getting up in the morning to defecate; more measurement time points for the impedance value and the body parameter are also It may include: before getting up in the morning to defecate and before going to bed; and/or, the behavior characteristics of the first day that the feedback module uses to feed back to the user include at least one of the following: the amount of food eaten by the user; Eating structure; the user’s eating and cooking method; the quality of the food eaten by the user; the user’s eating habits; the user’s work and rest conditions; the amount of activity of the user; Fatigue degree; analysis of energy and substance metabolism rules of the user's body.

The above program or software or system or device can run in the processor, or can also be stored in the memory (or called computer-readable medium), and the computer-readable medium includes permanent and non-permanent, removable and non-removable Media can be implemented by any method or technology for information storage. Information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Flash memory or other memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cartridge, tape magnetic disk storage or other magnetic storage device or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media excludes transitory computer-readable media, such as modulated data signals and carrier waves.

The above are merely examples of the present disclosure, and are not intended to limit the present disclosure. Various modifications and changes to the present disclosure will occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included within the scope of the claims of the present disclosure.

Claims

A user behavior feedback method based on energy state changes, including:

Acquiring at least two impedance values and at least two body parameters of the user's body measured within a predetermined period, wherein the body parameters are physiological parameters of the user;

Determining the energy state change of the user at least according to the at least two impedance values and the at least two body parameters, wherein the energy state change is used to indicate at least one of the following: energy intake, energy intake structure , energy consumption, energy consumption mode;

Determine the corresponding behavioral characteristics of the user according to predetermined information, and feed back to the user, wherein the behavioral characteristics are behavioral characteristics that cause changes in the energy state of the user, wherein the predetermined information includes at least the energy of the user state change.
The method according to claim 1, wherein the predetermined period is in days, the predetermined period includes at least two consecutive days, and at least two impedance values and at least two impedance values of the user's body are measured within the predetermined period Physical parameters include:

At least two impedance values and/or at least two body parameters of the user's body are obtained by measuring at a fixed time point and/or a time point at which a fixed behavior occurs every day within the predetermined period; and/or,

In the case where two impedance values and two body parameters are required, the two impedance values and the two impedance values and the Two body parameters.
The method according to claim 2, wherein the fixed time point of each day for obtaining the impedance value and the body parameter/or the measurement point where the fixed behavior occurs is after getting up in the morning to defecate; The time points for measuring the above physical parameters may also include: before getting up in the morning to defecate and before going to bed.
The method according to claim 3, further comprising:

Obtaining two consecutive groups of body impedance values and/or at least two groups of body parameters of the user, and the user's body impedance values and/or body parameters measured on the first day before going to bed, to obtain Three sets of measurement results;

The behavioral characteristics of the user on the first day are determined according to at least the three sets of measurement results, wherein the behavioral characteristics are behavioral characteristics made by the user that affect the change of the energy state.
The method according to claim 4, wherein the behavior characteristics of the first day determined based on at least the three sets of measurement results and fed back to the user include at least one of the following:

The amount of food eaten by the user; the eating structure of the user; the cooking method of the user eating; the quality of food eaten by the user; the eating habits of the user; The preference of the user's activity type; the degree of physical fatigue of the user; the analysis of the energy and substance metabolism of the user's body.
The method according to claim 1, wherein,

The predetermined information also includes at least one of the following: the impedance value, the body parameter; and/or,

The physical parameters include at least one of the following: weight, age, gender, and height information.
An electronic device, comprising:

A screen; used to display at least one of the following measured by any one of claims 1 to 6: physical parameters, impedance values, behavioral characteristics;

software, for carrying out the method described in any one in claim 1 to 6;

memory for storing said software;

a processor for running the software.
A user behavior feedback system based on energy state changes, including:

An acquisition module, configured to acquire at least two impedance values and at least two body parameters of the user's body measured within a predetermined period, wherein the body parameters are physiological parameters of the user;

A determining module, configured to determine a change in energy state of the user at least according to the at least two impedance values and the at least two physical parameters, wherein the change in energy state is used to indicate at least one of the following: energy intake , energy intake structure, energy consumption, energy consumption mode;

The feedback module determines the corresponding behavioral characteristics of the user according to predetermined information, and feeds back to the user, wherein the behavioral characteristics are behavioral characteristics that cause changes in the energy state of the user, and the predetermined information includes: the user's Energy state changes.
The system of claim 8, wherein,

The predetermined period is in units of days, and the predetermined period includes at least two consecutive days, and the acquisition module is used to perform measurement at a fixed time point and/or a time point when a fixed behavior occurs in each day within the predetermined period obtaining at least one impedance value and/or at least one body parameter of the user's body; and/or,

The acquisition module is used to obtain the two impedance values and two body parameters by performing measurements at the same time period on two adjacent days within the predetermined period and after the same fixed behavior occurs. an impedance value and the two body parameters; and/or,

The acquisition module is also used to acquire two consecutive sets of body impedance values and/or at least two sets of body parameters of the user, as well as the user's body impedance values measured on the first day before going to bed and/or or the physical parameters to obtain three sets of measurement results; the feedback module is also used to at least determine the behavioral characteristics of the user on the first day according to the three sets of measurement results, wherein the behavioral characteristics are that the user does behavioral characteristics that affect said energy state change; and/or,

The predetermined information also includes at least one of the following: the impedance value, the body parameter; and/or,

The physical parameters include at least one of the following: weight, age, gender, and height information.
The system of claim 9, wherein,

The fixed time point of each day for obtaining the impedance value and the body parameter/or the measurement point where the fixed behavior occurs is after getting up in the morning to defecate; more measurement time points for the impedance value and the body parameter may also include: in the morning before a bowel movement and before going to bed; and/or,

The behavior characteristics of the first day that the feedback module is used to feed back to the user include at least one of the following: the amount of food eaten by the user; the eating structure of the user; the cooking method of the user’s food; the food eaten by the user Quality; the user's eating habits; the user's work and rest status; the user's activity level; the user's activity type preference; the user's physical fatigue;