CN113241149A - User behavior feedback method and system based on energy state change - Google Patents
User behavior feedback method and system based on energy state change Download PDFInfo
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Abstract
The application discloses a user behavior feedback method and a system based on energy state change, wherein the method comprises the following steps: acquiring at least two impedance values and at least two body parameters of a user body measured in a preset period, wherein the body parameters are physiological parameters of the user; determining a change in an energy state of the user based at least on the at least two impedance values and the at least two physical parameters; and determining a corresponding behavior characteristic of the user according to the preset information, and feeding back the behavior characteristic to the user, wherein the behavior characteristic is a behavior characteristic causing the energy state change of the user, and the preset information at least comprises the energy state change of the user. Through the application, the problem caused by the fact that the weight is supervised by manpower in the prior art is solved, the effect of scientific supervision is achieved, and the improvement of the physical health of people is facilitated.
Description
Technical Field
The application relates to the field of software, in particular to a user behavior feedback method and system based on energy state change.
Background
Obesity has become a public health problem and the medical community has long demonstrated that lifestyle management is the only avenue for yang-related weight loss. But as soon as lifestyle management is concerned, people have a negative feeling of keeping hunger and a lot of exercise, being hard to stick to in the face of temptation, etc., so that few people are selected.
Users who want to lose weight generally want to be guided and supervised more professionally so that they can stay on for a long time.
Some professional weight-reducing mechanisms can achieve humanization through a large number of professional services, and help customers to change life styles in a personalized mode, but the cost of the services is high, and the services can not be enjoyed by all people.
Moreover, the method depends on the specialization of service personnel, and the requirement on the service personnel is higher.
Disclosure of Invention
The embodiment of the application provides a user behavior feedback method and system based on energy state change, so as to at least solve the problem caused by manually supervising weight loss in the prior art.
According to one aspect of the application, a user behavior feedback method based on energy state change is provided, and comprises the following steps: acquiring at least two impedance values and at least two body parameters of a user body measured in a preset period, wherein the body parameters are physiological parameters of the user; determining an energy state change of the user based at least on the at least two impedance values and the at least two body parameters, wherein the energy state change is indicative of at least one of: energy intake, energy intake structure, energy consumption pattern; and determining a corresponding behavior characteristic of the user according to predetermined information, and feeding back the behavior characteristic to the user, wherein the behavior characteristic is a behavior characteristic causing the energy state change of the user, and the predetermined information at least comprises the energy state change of the user.
Further, the predetermined period is in units of days, the predetermined period includes at least two consecutive days, and the at least two impedance values and the at least two body parameters of the user's body measured in the predetermined period include: measuring at least two impedance values and/or at least two body parameters of the user's body at fixed time points and/or at time points of occurrence of fixed behavior for each day within the predetermined period; and/or, in case two impedance values and two body parameters are required, measuring said two impedance values and said two body parameters after the same time period of two consecutive days within said predetermined period and the same said immobilization has taken place.
Further, the fixed time point of each day and/or the measurement point of the occurrence of the fixed behavior for obtaining the impedance value and the body parameter is after getting up and defecating in the morning; the measurement time points for further said impedance values and said body parameters may further comprise: before getting up to bed and defecating in the morning and before going to sleep.
Further, still include: acquiring two continuous groups of body impedance values and/or at least two groups of body parameters of the user, and the body impedance values and/or the body parameters of the user before sleep measured on the first day to obtain three groups of measurement results; determining a behavior feature of the user on a first day based at least on the three sets of measurements, wherein the behavior feature is a behavior feature made by the user that affects the change in energy state.
Further, the behavioral characteristics of the first day determined and fed back to the user based at least on the three sets of measurements include at least one of: the amount of food intake of the user is too much; the user feeding structure; the user eating cooking method; a food quality of the user's eating; the eating behavior habit of the user; the work and rest status of the user; the amount of activity of the user is large or small; the user activity type preference; the user's physical fatigue level; and analyzing the metabolic rule of the energy substance of the body of the user.
Further, the predetermined information further includes at least one of: the impedance value, the body parameter; and/or, the physical parameter comprises at least one of: weight, age, sex, height information.
According to another aspect of the present application, there is also provided an electronic device including: a screen; for displaying at least one of the following measured results: body parameters, impedance values, behavioral characteristics; software for performing the above-described method; a memory for storing the software; a processor for running the software.
According to another aspect of the present application, there is also provided a user behavior feedback system based on energy state change, including: the system comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring at least two impedance values and at least two body parameters of a body of a user, which are measured in a preset period, wherein the body parameters are physiological parameters of the user; a determination module for determining an energy state change of the user based on at least the at least two impedance values and the at least two body parameters, wherein the energy state change is indicative of at least one of: energy intake, energy intake structure, energy consumption pattern; the feedback module is used for determining the corresponding behavior characteristics of the user according to preset information and feeding back the behavior characteristics to the user, wherein the behavior characteristics are behavior characteristics causing the energy state change of the user, and the preset information comprises: the energy state of the user changes.
Further, the predetermined period is in units of days, the predetermined period includes at least two days, and the obtaining module is configured to measure at least two impedance values and/or at least two body parameters of the body of the user at a fixed time point and/or a time point at which a fixed behavior occurs on each day in the predetermined period; and/or the acquisition module is used for measuring two impedance values and two body parameters after the same time periods of two adjacent days in the preset period and the same fixed behavior are generated under the condition that the two impedance values and the two body parameters are needed; and/or the obtaining module is further configured to obtain two consecutive groups of body impedance values and/or at least two groups of body parameters of the user, and the body impedance values and/or the body parameters of the user before sleep measured on the first day, so as to obtain three groups of measurement results; the feedback module is further used for determining the behavior characteristic of the user on the first day at least according to the three groups of measurement results, wherein the behavior characteristic is the behavior characteristic which is made by the user and influences the energy state change; and/or, the predetermined information further comprises at least one of: the impedance value, the body parameter; and/or, the physical parameter comprises at least one of: weight, age, sex, height information.
Further, the fixed time point of each day and/or the measurement point of the occurrence of the fixed behavior for obtaining the impedance value and the body parameter is after getting up and defecating in the morning; the measurement time points for further said impedance values and said body parameters may further comprise: before getting up and defecating in the morning and before going to sleep; and/or the feedback module is used for feeding back the behavior characteristics of the first day to the user, and the behavior characteristics of the first day comprise at least one of the following characteristics: the amount of food intake of the user is too much; the user feeding structure; the user eating cooking method; a food quality of the user's eating; the eating behavior habit of the user; the work and rest status of the user; the amount of activity of the user is large or small; the user activity type preference; the user's physical fatigue level; and analyzing the metabolic rule of the energy substance of the body of the user.
In the embodiment of the application, at least two impedance values and at least two body parameters of a body of a user, which are measured in a predetermined period, are obtained, wherein the body parameters are physiological parameters of the user; determining an energy state change of the user based at least on the at least two impedance values and the at least two body parameters, wherein the energy state change is indicative of at least one of: energy intake, energy intake structure, energy consumption pattern; and determining a corresponding behavior characteristic of the user according to predetermined information, and feeding back the behavior characteristic to the user, wherein the behavior characteristic is a behavior characteristic causing the energy state change of the user, and the predetermined information at least comprises the energy state change of the user. Through the application, the problem caused by the fact that the weight is supervised by manpower in the prior art is solved, the effect of scientific supervision is achieved, and the improvement of the physical health of people is facilitated.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
fig. 1 is a flowchart of a method for user behavior feedback based on energy state changes according to an embodiment of the present application.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
The health lifestyle is difficult to understand because people usually only pay attention to timely feedback and take action, but bad lifestyles have great hysteresis and profound understanding on health, so people do not pay enough attention to bad habits in lifestyles; meanwhile, because the age, sex, gene and living environment of each person are different, and the influence degree of the same life style on each person is different, although many people know the general principle of healthy life, specific living details of the people often have no specific method, so that people have no way to start with the life. The method provided by the embodiment can be scaled, and the common people can easily, naturally and effortlessly adjust the life style at low cost, so that the health is obtained.
In this embodiment, a user behavior feedback method based on energy state change is provided, and fig. 1 is a flowchart of the user behavior feedback method based on energy state change according to the embodiment of the present application, and as shown in fig. 1, the flowchart includes the following steps:
step S102, acquiring at least two resistance values and at least two body parameters of the body of the user, wherein the resistance values and the body parameters are measured in a preset period, and the body parameters are physiological parameters of the user;
step S104, determining an energy state change of the user according to at least two resistance values and at least two body parameters, wherein the energy state change is used for indicating at least one of the following: energy intake, energy intake structure, energy consumption pattern;
the resistance value is used in the above steps, because each different body state corresponds to a different resistance value, the body state of the user can be determined by the resistance value, and in order to ensure more accurate determination of the energy state, a body parameter can be added, and the body parameter can include but is not limited to at least one of the following: weight, age, sex, height information. Alternatively, the resistance value is an impedance value of a human body. Preferably, the impedance value of the body below the waist and abdomen (inclusive) or the variation of the impedance value of the body may be further described.
In the above steps, the energy state may be obtained according to the physiological parameter and the resistance value, and then the change between the plurality of energy states may be obtained according to the plurality of energy states.
In an alternative, the collected user data (for example, data stored in a medical institution and authorized by the obtained user) can be used as training data, and each set of training data includes a physiological parameter such as height and weight of the user, a resistance value, and a fat parameter corresponding to the physiological parameter and the resistance value, wherein the fat parameter is used for indicating the fat content (for example, body fat rate and/or muscle mass) of the user. When the number of training data exceeds a threshold, the training data may be sent to a machine learning engine for training.
The machine learning engine can adopt the existing machine learning engine, the specific engine building and running process can participate in the technical manuals of each engine, and technicians in the field can build the corresponding machine learning engine according to the technical manuals. After the machine learning engine is trained by using a plurality of groups of training data, a machine-learned first model can be obtained. After the model is obtained, the fat parameter of the user can be obtained by using the model, and the first model can output the corresponding fat parameter by inputting the physiological parameter and the resistance value of the user into the first model.
The energy state of the user is then derived from the fat parameter and the physiological parameter as described above. In the above example a fat parameter is used, which may also be considered as one of the physiological parameters, if the user directly inputs the fat parameter, the energy status may be obtained according to the following example.
As another alternative, now that the machine learning engine has been used, the machine learning engine may be used to train a second model, each of the sets of training data used to train the model including the fat parameter and the physiological parameter of the user and the energy state corresponding to the fat parameter and the physiological parameter. After the second model is obtained through training, the corresponding energy state can be obtained only by inputting the fat parameter and the physiological parameter.
The resulting energy status may also be displayed to the user for the user's own perception. If the energy state does not need to be displayed to the user, a third model may be used, each of the sets of training data used to train the model including the fat parameter and the physiological parameter of the user and the behavior recommendation corresponding to the fat parameter and the physiological parameter. The third model is different from the second model in that the behavior suggestion is directly output by the model. After the second model is obtained through training, corresponding behavior suggestions can be obtained only by inputting the fat parameters and the physiological parameters.
After the energy state is obtained, a change in energy state can be obtained based on at least two energy states.
Step S106, determining the corresponding behavior characteristics of the user according to the preset information, and feeding back the behavior characteristics to the user, wherein the behavior characteristics cause the energy state change of the user; wherein the predetermined information at least includes: the energy state of the user changes. Optionally, the predetermined information may further include: a physiological parameter and/or a resistance value.
The machine learning engine-based model in the above alternative embodiment is used after a large amount of training data is accumulated, and if the amount of training data is insufficient, a pre-configured correspondence may be used, for example, the energy state may be acquired according to a pre-configured correspondence of the resistance value, the body parameter, and the energy state. These correspondences may be measured in advance by accurate measurement means. Alternatively, various measured data may be fitted to a function by software, and the energy state output by the function may be obtained by using the resistance value and the body parameter as the input of the function.
For the determination of the behavior feature, the determination may also be performed according to a relationship between predetermined information and the behavior feature, which is configured in advance. The relationship between the pre-configured predetermined information and the behavior characteristics is obtained through statistics of the samples. When the number of samples reaches a level at which machine learning training is possible, a machine learning model, which may be referred to as a behavior feature model, may be trained to obtain behavior features from predetermined information. The behavior feature model is obtained by training a plurality of groups of training data, each group of training data comprises preset information and a label, and the label is used for identifying the behavior feature under the preset information. A convergent behavior feature model is obtained through training and can be used after verification of verification data, and the verification data also come from sample data. The predetermined information in step S106 is input into the behavior feature model, and the behavior feature model may input a label indicating the behavior feature.
Regardless of the implementation used, the user can be provided with behavior advice by measuring each cycle, as long as the energy (or heat) handling capacity of a user is determined by the cooperation of the resistance value and the physical parameter in the above steps. The processing power may also be understood to include how much calories are ingested and how much calories are consumed by the user. The behavior characteristic model can directly obtain the behavior characteristic, and for the change of the energy state, the change of the energy state can be determined by comparison after the energy state is obtained. The above description has been made, and will not be described herein.
In this embodiment, the processing may also be performed by a classification method, for example, at least one of the following may be sorted and classified: the direction and/or magnitude of the change in body impedance, and the direction and/or magnitude of the change in body parameter, at predetermined times, are combined, and the classification is based on the fact that each combination of changes can correspond to a particular behavioral characteristic that causes the change. For example, caloric intake exceeds a predetermined standard value, and the behavior corresponds to a combination of multiple sets of impedance changes and/or body parameter changes. Therefore, the behavior characteristics of the current life style of the user can be reversely deduced by measuring the body impedance and the change of the body parameters in the preset time.
The classification method can also be classified in various ways, for example, by the machine learning method.
The model trained by machine learning may be referred to as a classification model, and the classification model is trained by a plurality of sets of training data, each set of training data includes a specific behavior feature and a change in body impedance and/or body parameter caused by the behavior feature. Taking the specific behavior characteristics as input, taking the change of the body impedance and/or the body parameters as output, and determining the change of the body impedance and/or the body parameters according to the behavior characteristics by using the trained model; the trained model can be used for outputting the behavior characteristics according to the changes of the body impedance and/or the body parameters by taking the changes of the body impedance and/or the body parameters as input and taking the specific behavior characteristics as output.
When the classification is carried out, the correspondence with the behavior characteristics can be further classified and corresponding according to gender, age, height, living environment and the like.
As another mode, body composition changes can be deduced by combining body impedance changes with body parameter changes, and then behavior characteristics in the lifestyle can be deduced by the body composition changes; this derivation can also be understood as a classification method, and unlike the above-described embodiment, classification is performed twice. The specific adopted mode is the same as the above embodiment, and is not described herein again. The body composition herein may include at least one of: body fat rate, muscle mass, skeletal muscle rate, lactone, BMI, body water, protein, bone mass; variables in the physical parameters may include blood pressure, blood sugar, etc. in addition to body weight, and other parameters are not listed here.
The above steps may be run in a program, which may be an application installed in the mobile device, a software installed in a personal computer, or a service running on a server. In the following embodiments, software, applications, services are all referred to as software. The software is used for judging and pushing behavior suggestions, so that large-scale application can be realized, and the software is not limited by the number and the capability of professional service personnel. In addition, the behavior suggestion is very easy to obtain for the user on one hand, and on the other hand, the software is the behavior suggestion obtained based on objective physical values, and is more scientific. Therefore, the problems caused by manually supervising the weight loss in the prior art are solved through the steps, the effect of scientific supervision is achieved, and the improvement of the body health of people is facilitated.
In an alternative embodiment, the predetermined period may be in units of days, for example, the predetermined period may include at least two consecutive days. Measuring at least two impedance values and/or at least two body parameters of the user's body at fixed time points of each day within the predetermined period and/or at time points at which fixed behaviors occur, if measured by day; . For example, measurements were taken at 7, 9 and 11 am per day. This manner of measurement may establish a time-to-resistance value versus a body parameter. However, this measurement is not a very accurate value because the behavior of each user at different time points is different, and in order to find a more reasonable measurement point, this embodiment may choose to take measurements after getting up and defecating every morning, and optionally, if multiple data of a day are needed, the following behavior may be added: the resistance values and/or body parameters of the body of the user before defecation and before sleep after getting up in the morning of each day are measured. If two impedance values and two body parameters are needed, the two impedance values and the two body parameters are obtained by measuring in the same time period of two adjacent days in the preset period and after the same fixed behavior occurs.
As another optional implementation, when the user uses the apparatus for the first time, three sets of measurement results may be obtained according to the two consecutive sets of body impedance values and/or at least two sets of body parameters of the user, and the body impedance values and/or the body parameters of the user before going to sleep measured on the first day; determining a behavior feature of the user on a first day based at least on the three sets of measurements, wherein the behavior feature is a behavior feature made by the user that affects the change in energy state.
As another alternative, since the measurement is performed every day, the current day behavior of the user can be determined based on the measurement results obtained from the measurement performed every day. For example, resistance values and/or at least one body parameter of the body of the user after getting up in the morning, after getting up in the morning and after defecating and before sleeping are measured on the same day by the user are obtained to obtain three groups of measurement results; and determining the behavior characteristics of the user in the current day according to at least three groups of measurement results.
In one example, the physical state of the user may be determined from the difference in fat and the difference in muscle mass on alternate days. Specifically, when the alternate-day fat difference is not a negative value and the alternate-day muscle difference is not a positive value, it indicates that the body fat of the user is not increased and the muscle is not decreased, and thus it is determined that the body state of the user is normal; otherwise, the body state of the user is judged to be abnormal, and then the reason causing the body state of the user to be abnormal is judged to be excessive drinking water or lack of drinking water according to the resistance value.
In order to obtain more accurate reasons, the behavior of the user in the current day can be determined according to the three groups of measurement results; receiving feedback of a user on the real behaviors of the current day; and determining the current-day behavior of the user according to the first current-day behavior of the user and the feedback. For example, the user may be asked to enter water intake and further decisions may be made based on the water intake entered by the user.
The behavior characteristics determined by the above example based on the change in the energy state of the user may be displayed to the user. The behavior feature may include at least one of: the amount of food intake of the user is too much; the user feeding structure; the user eating cooking method; a food quality of the user's eating; the eating behavior habit of the user; the work and rest status of the user; the amount of activity of the user is large or small; the user activity type preference; the user's physical fatigue level; and analyzing the metabolic rule of the energy substance of the body of the user.
The various steps and/or functions described above are described below in connection with a preferred embodiment. This preferred embodiment incorporates some or all of the above-described alternative embodiments.
The behavior feedback software comprises a measuring device capable of measuring the body weight and the body impedance at one time and a data sending module, and the measured body weight and body impedance values can be sent to the data processing module. The data processing module can give corresponding feedback information according to the measurement of different periods, different times, different states and different contexts of the user.
The body state of the human body at any time point is the accumulated result of all life styles accumulated in the past day and month, so after the user measures for the first time, the data analysis module deduces the characteristic summary of the past behavior of the user to be shown according to the weight, impedance, age, sex and height information of the user, and the characteristic summary is used as the first feedback to the user. Through this feedback, the user is made aware of the direct association of his current physical state with lifestyle behavior. Subsequently, the software will give the user the best and sub-best body weight, body fat and lactone standard ranges according to the user's age, gender and time required to reach each stage, give the user the wishes according to the general criteria and guide him to give his commitments.
Next, the software gives the user an actual exercise scheme obtained according to the national standard dietary guidelines, so that the user can adjust the diet of the user to create a caloric gap according to the understanding of the user, at the moment, the data acquisition module can count the weight (3) values of the user from morning (1), after morning and night (2) and before sleep, and count the average value and daily deviation value of the difference value between the values every day. Taking 3-7 days as a statistical period, and then giving a second feedback point of the user, namely the energy intake and consumption balance overall state of the body, specifically the intake capacity and the consumption capacity of the user, wherein the consumption capacity is divided into basic metabolic capacity, digestive capacity, consumption capacity and food heat effect capacity.
And combining the observed user ability analysis, the system gives a scheme suggestion customized according to the user, the system has a manual coach interface, and the manual coach can select a method which is easy to execute by the user and can reach a heat gap from the scheme suggestion according to the meal card punching content of the user, give the user and supervise the execution of the method.
After the user starts to execute the system, the system can automatically position bad behaviors influencing the body on the day according to the weight and impedance measured three times a day by the user and corresponding information such as age, sex, height and the like, and timely give feedback through the interactive design of the system. Thereby making the user feel and adjust voluntarily.
The difference between the present software and traditional BIA analysis is that the present software is dedicated to studying the precise reaction of data changes to daily behavior and to guiding the user to change behavior consciously through appropriate feedback, rather than pursuing the accuracy of the body static data.
The software in the preferred embodiment can accurately position the user behavior based on the body impedance and weight data, and prompt the user to change his own behavior by conscious and spontaneous actions through a series of accurate feedback point settings and implicit guidance. Most critically, for the user, all feedback points can be unlocked as long as weight and body impedance measurements are taken every few tens of seconds from ceiling. Therefore, large-scale life style management is realized, and more people can have a determined effect at low cost.
In this embodiment, there is also provided an electronic device comprising a memory and/or a processor, the memory having software stored therein, the processor being configured to execute the software to perform the method in the above embodiments. The electronic device may further include: and (6) a screen. The screen is used to display relevant information, e.g. for displaying the measured body parameters, resistance values, behaviour and/or behaviour recommendations. If the screen is a touch screen, the screen can also be used as an input device, and various information can be input through the screen. Of course, the electronic apparatus may also comprise other types of input devices, such as a physical or virtual keyboard, for example, and a microphone, by means of which voice commands can be input.
The software may also be referred to as a computer program which may be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks, and corresponding steps may be implemented by different modules. The software or program may also be referred to as a device or system.
In this embodiment, a system for feedback of user behavior based on energy state change is further provided, including: a system for user behavior feedback based on changes in energy state, comprising: the system comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring at least two impedance values and at least two body parameters of a user body measured in a preset period, and the body parameters are physiological parameters of the user; a determination module for determining an energy state change of the user based on at least the at least two impedance values and the at least two body parameters, wherein the energy state change is indicative of at least one of: energy intake, energy intake structure, energy consumption pattern; the feedback module is used for determining the corresponding behavior characteristics of the user according to the preset information and feeding back the behavior characteristics to the user, wherein the behavior characteristics are the behavior characteristics causing the energy state change of the user; wherein the predetermined information at least includes: the energy state of the user changes. Optionally, the predetermined information may further include: a physiological parameter and/or a resistance value.
The modules in the feedback system correspond to the steps in the method, which have been described in the method and are not described herein again.
Preferably, the predetermined period is in units of days, the predetermined period includes at least two consecutive days, and the obtaining module is configured to measure at least two impedance values and/or at least two body parameters of the body of the user at a fixed time point and/or a time point at which a fixed behavior occurs on each day in the predetermined period; and/or the acquisition module is used for measuring two impedance values and two body parameters after the same time periods of two adjacent days in a preset period and the same fixed behaviors occur under the condition that the two impedance values and the two body parameters are needed; and/or the acquisition module is further used for acquiring two continuous groups of body impedance values and/or at least two groups of body parameters of the user, and the body impedance values and/or the body parameters of the user before sleep measured on the first day to obtain three groups of measurement results; the feedback module is further used for determining the behavior characteristics of the user on the first day according to at least the three groups of measurement results, wherein the behavior characteristics are the behavior characteristics which are made by the user and influence the energy state change.
Preferably, the fixed time point of each day and/or the measurement point at which the fixed behavior occurs for obtaining the impedance value and the body parameter is after getting up and defecating in the morning; the measurement time points for further said impedance values and said body parameters may further comprise: before getting up and defecating in the morning and before going to sleep; and/or the feedback module is used for feeding back the behavior characteristics of the first day to the user, and the behavior characteristics of the first day comprise at least one of the following characteristics: the amount of food intake of the user is too much; the user feeding structure; the user eating cooking method; a food quality of the user's eating; the eating behavior habit of the user; the work and rest status of the user; the amount of activity of the user is large or small; the user activity type preference; the user's physical fatigue level; and analyzing the metabolic rule of the energy substance of the body of the user.
The above-described programs or software or systems or devices may be run on a processor or may also be stored in a memory (or referred to as a computer-readable medium), which may include non-transitory and non-transitory, removable and non-removable media, that implement information storage by any method or technology. The 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 Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A user behavior feedback method based on energy state change is characterized by comprising the following steps:
acquiring at least two impedance values and at least two body parameters of a user body measured in a preset period, wherein the body parameters are physiological parameters of the user;
determining an energy state change of the user based at least on the at least two impedance values and the at least two body parameters, wherein the energy state change is indicative of at least one of: energy intake, energy intake structure, energy consumption pattern;
and determining a corresponding behavior characteristic of the user according to predetermined information, and feeding back the behavior characteristic to the user, wherein the behavior characteristic is a behavior characteristic causing the energy state change of the user, and the predetermined information at least comprises the energy state change of the user.
2. The method according to claim 1, wherein the predetermined period is in units of days, the predetermined period comprises at least two consecutive days, and the at least two impedance values and at least two body parameters of the user's body measured during the predetermined period comprise:
measuring at least two impedance values and/or at least two body parameters of the user's body at fixed time points and/or at time points of occurrence of fixed behavior for each day within the predetermined period; and/or the presence of a gas in the gas,
in case two impedance values and two body parameters are required, the two impedance values and the two body parameters are obtained by measuring at the same time period of two adjacent days within the predetermined period and after the same fixation behavior occurs.
3. The method according to claim 2, wherein the fixed time point/or the measurement point at which a fixed behavior occurs for each day at which the impedance value and body parameter are obtained is after morning wake up; the measurement time points for further said impedance values and said body parameters may further comprise: before getting up to bed and defecating in the morning and before going to sleep.
4. The method of claim 3, further comprising:
acquiring two continuous groups of body impedance values and/or at least two groups of body parameters of the user, and the body impedance values and/or the body parameters of the user before sleep measured on the first day to obtain three groups of measurement results;
determining a behavior feature of the user on a first day based at least on the three sets of measurements, wherein the behavior feature is a behavior feature made by the user that affects the change in energy state.
5. The method of claim 4, wherein the first day's behavioral characteristics determined and fed back to the user based at least on the three sets of measurements comprises at least one of:
the amount of food intake of the user is too much; the user feeding structure; the user eating cooking method; a food quality of the user's eating; the eating behavior habit of the user; the work and rest status of the user; the amount of activity of the user is large or small; the user activity type preference; the user's physical fatigue level; and analyzing the metabolic rule of the energy substance of the body of the user.
6. The method of claim 1,
the predetermined information further includes at least one of: the impedance value, the body parameter; and/or the presence of a gas in the gas,
the physical parameter comprises at least one of: weight, age, sex, height information.
7. An electronic device, comprising:
a screen; for displaying at least one of the following measured according to any one of claims 1 to 6: body parameters, impedance values, behavioral characteristics;
software for performing the method of any one of claims 1 to 6;
a memory for storing the software;
a processor for running the software.
8. A system for user behavior feedback based on changes in energy state, comprising:
the system comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring at least two impedance values and at least two body parameters of a body of a user, which are measured in a preset period, wherein the body parameters are physiological parameters of the user;
a determination module for determining an energy state change of the user based on at least the at least two impedance values and the at least two body parameters, wherein the energy state change is indicative of at least one of: energy intake, energy intake structure, energy consumption pattern;
the feedback module is used for determining the corresponding behavior characteristics of the user according to preset information and feeding back the behavior characteristics to the user, wherein the behavior characteristics are behavior characteristics causing the energy state change of the user, and the preset information comprises: the energy state of the user changes.
9. The system of claim 8,
the predetermined period is in units of days, the predetermined period comprises at least two consecutive days, and the acquisition module is used for measuring at least one impedance value and/or at least one body parameter of the body of the user at a fixed time point and/or a time point of occurrence of a fixed behavior of each day in the predetermined period; and/or the presence of a gas in the gas,
the acquisition module is used for measuring two impedance values and two body parameters after the same time periods of two adjacent days in the preset period and the same fixed behaviors occur under the condition that the two impedance values and the two body parameters are needed; and/or the presence of a gas in the gas,
the acquisition module is further configured to acquire two consecutive groups of body impedance values and/or at least two groups of body parameters of the user, and the body impedance values and/or the body parameters of the user before sleep measured on the first day, so as to obtain three groups of measurement results; the feedback module is further used for determining the behavior characteristic of the user on the first day at least according to the three groups of measurement results, wherein the behavior characteristic is the behavior characteristic which is made by the user and influences the energy state change; and/or, the predetermined information further comprises at least one of: the impedance value, the body parameter; and/or the presence of a gas in the gas,
the physical parameter comprises at least one of: weight, age, sex, height information.
10. The system of claim 9,
obtaining the impedance value and the body parameter, wherein the fixed time point of each day and/or the measuring point of the occurrence of the fixed behavior is after getting up and defecating in the morning; the measurement time points for further said impedance values and said body parameters may further comprise: before getting up and defecating in the morning and before going to sleep; and/or the presence of a gas in the gas,
the feedback module is used for feeding back the behavior characteristics of the first day to the user, and the behavior characteristics of the first day comprise at least one of the following: the amount of food intake of the user is too much; the user feeding structure; the user eating cooking method; a food quality of the user's eating; the eating behavior habit of the user; the work and rest status of the user; the amount of activity of the user is large or small; the user activity type preference; the user's physical fatigue level; and analyzing the metabolic rule of the energy substance of the body of the user.
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