Disclosure of Invention
The application provides a weight reduction analysis method and a weight reduction analysis system for an electronic scale based on AI intelligence, which aim to solve the technical problems.
The application provides a weight-reduction analysis method for an electronic scale based on AI intelligence, which comprises the steps of obtaining a multi-frequency bioelectrical impedance data set, a sole state data set and user basic information, analyzing the multi-frequency bioelectrical impedance data set and the sole state data set based on the user basic information, determining multi-dimensional physiological data, determining a multi-dimensional index change rate according to the multi-dimensional physiological data and historical physiological data, analyzing health sustainability of a current weight-reduction strategy of a user according to the multi-dimensional index change rate, evaluating sustainability of the weight-reduction strategy, and determining and outputting a weight-reduction state evaluation report according to the sustainability of the weight-reduction strategy and the multi-dimensional index change rate.
According to the technical scheme, the multi-frequency bioelectrical impedance data set, the sole state data set and the user basic information are comprehensively analyzed, multi-dimensional physiological data capable of comprehensively reflecting the weight reduction state of the user is determined, the problems that the bioelectrical impedance data obtained by the existing bioelectrical impedance analysis technology applied to the electronic scale are low in accuracy and easily affected by external factors are solved, scientificity and comprehensiveness of evaluation on the weight reduction strategy of the user are remarkably improved, health sustainability analysis is conducted on the weight reduction strategy of the user based on multi-dimensional index change rate, and a weight reduction state evaluation report is determined and output according to the sustainability of the weight reduction strategy and the multi-dimensional index change rate, so that the situation that the user damages body health and is not known by the weight reduction strategy is effectively avoided, and the accuracy of analysis on the weight reduction strategy is improved.
Optionally, the sole state data set comprises sole wettability, sole temperature and stratum corneum thickness, the multi-frequency bioelectrical impedance data set and the sole state data set are analyzed based on the user basic information, multi-dimensional physiological data are determined, the multi-frequency bioelectrical impedance data set is divided according to a preset frequency band set, a plurality of bioelectrical impedance values corresponding to different frequency bands are determined, the plurality of bioelectrical impedance values are calibrated in a targeted mode based on the different frequency bands according to the sole wettability, the sole temperature and the stratum corneum thickness, a plurality of calibrated bioelectrical impedance values are determined, and the plurality of calibrated bioelectrical impedance values are analyzed based on the user basic information, so that the multi-dimensional physiological data are determined.
According to the technical scheme, based on different frequency bands, the bioelectrical impedance values corresponding to different frequency bands are calibrated in a targeted mode according to the sole wettability, the sole temperature and the stratum corneum thickness, different influences from the sole states of users on bioelectrical impedance values measured under different frequency band currents are fully considered, the obtained bioelectrical impedance values are more in line with the actual impedance states in the users, the calibrated bioelectrical impedance values are analyzed based on user basic information, multidimensional physiological data are obtained, individual differences among different users are fully considered, and scientificity of the multidimensional physiological data is improved.
Optionally, the determining a plurality of calibrated bioelectrical impedance values based on the different frequency bands includes determining a frequency band influence coefficient corresponding to each frequency band according to the different frequency bands, determining the calibrated bioelectrical impedance value corresponding to each frequency band based on the frequency band influence coefficient according to the sole wettability, the sole temperature and the cuticle thickness, specifically including the following formulas:
;
Wherein,For the calibrated bioelectrical impedance value corresponding to the current frequency band,For the bioelectrical impedance value corresponding to the current frequency band,For the frequency band influence coefficient corresponding to the current frequency band,For the preset humidity influence coefficient,For the degree of wetness of the sole of the foot,For the preset thickness influence coefficient,For the thickness of the stratum corneum to be the same,In order to preset the temperature influence coefficient,Is the sole temperature.
According to the technical scheme, the bioelectrical impedance value corresponding to each frequency band is calibrated in a targeted mode through a mathematical formula according to the sole wettability, the sole temperature and the stratum corneum thickness by utilizing a mathematical analysis means based on the frequency band influence coefficient corresponding to each frequency band, so that the calibrated bioelectrical impedance value is obtained, errors caused by the influence of the sole state on bioelectrical impedance values of different frequency bands are effectively reduced, and the accuracy of multidimensional physiological data obtained by subsequent analysis based on the calibrated bioelectrical impedance values is improved.
Optionally, the user basic information comprises height, real-time weight, resting heart rate, age and sex factor, the method comprises analyzing a plurality of calibrated bioelectrical impedance values based on the user basic information, determining multidimensional physiological data, wherein the method comprises the steps of respectively extracting bioelectrical impedance values corresponding to the highest frequency and the lowest frequency according to the plurality of calibrated bioelectrical impedance values, determining a high-frequency impedance value and a low-frequency impedance value, analyzing the plurality of calibrated bioelectrical impedance values, determining an average impedance value, determining a user body fat rate according to the low-frequency impedance value, the average impedance value and the real-time weight based on the height, the age and the sex factor, analyzing the height, the high-frequency impedance value and the average impedance value, determining body muscle content according to the height, the user body fat rate and the average impedance value, and taking the real-time weight, the resting heart rate, the body water content and the body muscle content as the multidimensional physiological data.
According to the technical scheme, three representative bioelectrical impedance values of the low-frequency impedance value, the average impedance value and the high-frequency impedance value are utilized, the body fat rate, the body water content and the body muscle content of the user are respectively analyzed and quantified in different combination modes by combining the basic information of the user, the accuracy of in-vivo data analysis of the user is improved, and the real-time body weight, the resting heart rate, the body fat rate, the body water content and the body muscle content of the user are taken as multidimensional physiological data, so that the subsequent weight reduction strategy analysis based on the multidimensional physiological data can comprehensively reflect whether the current weight reduction strategy of the user is sustainable.
Optionally, the determining, based on the height, the age and the sex factor, a body fat rate of the user according to the low frequency impedance value, the average impedance value and the real-time weight is specifically the following formula:
;
Wherein,For the body fat percentage of the user,For the height of the person in question,For the value of the high-frequency impedance,For the preset high-frequency impact index,As a result of the value of the average impedance,In order to preset the first impedance impact index,For the preset age-affecting factor,For the said age of the patient in question,In order to be able to use the said sex factor,For the real-time body weight.
Through the technical scheme, the mathematical analysis means is utilized, based on the height, age and sex factors, the user body fat rate is scientifically and precisely quantified according to the low-frequency impedance value, the average impedance value and the real-time weight through a mathematical formula, the accuracy of the user body fat rate numerical value is improved, and meanwhile, the individual differences caused by the user body size, age and sex are fully considered, so that the calculated user body fat rate highly accords with the actual situation of the user.
Optionally, the analyzing the height, the high-frequency impedance value and the average impedance value determines the in-vivo moisture content, specifically by the following formula:;
Wherein,For the in-vivo moisture content of the said body,For the preset low-frequency influence coefficient,For the height of the person in question,For the value of the low-frequency impedance,For the preset low frequency impact index,In order to preset the impedance influence coefficient,As a result of the value of the average impedance,Is a preset second impedance impact index.
Through the technical scheme, the mathematical analysis means is utilized, the in-vivo moisture content of the current user is precisely quantified through a mathematical formula on the basis of the height, the high-frequency impedance value and the average impedance value, the scientificity of the in-vivo moisture content analysis process of the user is remarkably improved, and the accuracy of the subsequent weight reduction strategy analysis is further improved.
Optionally, the determining the muscle content in the body according to the height, the body fat rate of the user and the average impedance value is specifically the following formula:;
Wherein,For the in vivo muscle content of the subject,In order to preset the height influence coefficient,For the height of the person in question,As a result of the value of the average impedance,In order to preset the height influence index,In order to preset the body fat influence coefficient,For the body fat percentage of the user,In order to preset the body fat impact index,Is a preset adjustment coefficient.
Through the technical scheme, the in-vivo muscle content of the user is precisely quantified through a mathematical formula by utilizing a mathematical analysis means according to the height, the body fat rate and the average impedance value of the user, so that a scientific muscle content value which accords with the current in-vivo condition of the user is obtained, and the accuracy of the subsequent weight reduction strategy analysis process is further improved.
The method comprises the steps of determining a compound influence index according to the water content change rate and the muscle change rate, determining a sustainable index according to the compound influence index, the body weight change rate, the body fat change rate and the heart rate change rate, comparing the sustainable index with a preset ideal index range, judging whether the sustainable index is in the preset ideal index range, determining that the sustainable index is sustainable if the sustainable index is in the preset ideal index range, and determining that the sustainable strategy is not sustainable if the sustainable index is not in the preset ideal index range.
According to the technical scheme, the weight change rate, the body fat change rate, the heart rate change rate and the composite influence index reflecting the combined action of the moisture content and the muscle mass are synthesized, the sustainable index reflecting the sustainability of the weight reduction strategy is scientifically analyzed to accurately reflect the sustainability of the current weight reduction strategy of the user, and whether the current weight reduction strategy of the user is sustainable or not is accurately judged by comparing the sustainable index with the preset ideal index range, so that the user can know whether the currently used weight reduction strategy is sustainable or not in time.
Optionally, the determining a sustainable index according to the composite impact index, the weight change rate, the body fat change rate and the heart rate change rate is specifically the following formula:
;
Wherein,In order for the sustainable index to be a function of the above,For the rate of change of the body weight,In order to preset the ideal weight change rate,For the rate of change of body fat in question,In order to preset the ideal body fat change rate,For the preset heart rate influencing factor,For the rate of change of the heart rate,For the composite impact index to be described,In order to achieve the rate of change of the moisture,Determining a composite influence index according to the water content change rate and the muscle change rate, wherein the composite influence index is specifically represented by the following formula:;
Wherein,For the composite impact index to be described,In order to achieve the rate of change of the moisture,For the rate of change of the muscle to be described,To preset the ideal moisture change rate.
Through the technical scheme, the sustainable index is precisely quantized through a mathematical formula by utilizing a mathematical analysis means according to the composite influence index, the weight change rate, the body fat change rate and the heart rate change rate, and meanwhile, the quantization process of the composite influence index is explicitly developed through the mathematical formula, so that the scientificity and the accuracy of the sustainable analysis process of the weight reduction strategy of the user are ensured.
In a second aspect, the present application provides a weight-reduction analysis system for an electronic scale based on AI intelligence, the system comprising:
The multidimensional analysis module is used for acquiring a multi-frequency bioelectrical impedance data set, a sole state data set and user basic information, analyzing the multi-frequency bioelectrical impedance data set and the sole state data set based on the user basic information, and determining multidimensional physiological data;
the change analysis module is used for determining the change rate of the multidimensional index according to the multidimensional physiological data and the historical physiological data;
the sustainable analysis module is used for carrying out health sustainability analysis on the current weight-reduction strategy of the user according to the multi-dimensional index change rate and evaluating the sustainability of the weight-reduction strategy;
and the report output module is used for determining and outputting a weight-reduction state evaluation report according to the sustainability of the weight-reduction strategy and the multi-dimensional index change rate.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" is merely an association relation describing the association object, and means that three kinds of relations may exist, for example, a and/or B, and that three kinds of cases where a exists alone, while a and B exist alone, exist alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Embodiments of the application are described in further detail below with reference to the drawings.
The existing electronic scale still only bears simple work of monitoring and outputting weight data, and a user adopting an extreme weight reduction measure can easily obtain false positive feedback from the weight change data of simple dimension provided by the electronic scale, so that the user is affected by the continuous unreasonable weight reduction measure in the weight reduction process to damage the health of the user.
Based on the analysis method, the application provides an AI intelligent-based weight reduction analysis method for the electronic scale. The multi-frequency bioelectrical impedance data set, the sole state data set and the user basic information are comprehensively analyzed, multi-dimensional physiological data capable of comprehensively reflecting the weight reduction state of the user is determined, the problems that bioelectrical impedance data obtained by the existing bioelectrical impedance analysis technology applied to the electronic scale are low in accuracy and easy to influence by external factors are solved, scientificity and comprehensiveness of evaluation of a weight reduction strategy of the user are remarkably improved, health sustainability analysis is conducted on the weight reduction strategy of the user based on multi-dimensional index change rate, and a weight reduction state evaluation report is determined and output according to the sustainability of the weight reduction strategy and the multi-dimensional index change rate, so that the situation that the user damages body health by adopting an extreme weight reduction strategy and is not self-known is effectively avoided, and accuracy of analysis on the weight reduction strategy is improved.
Fig. 1 is a schematic diagram of an application scenario provided by the application, in which the method of the application is applied to accurately evaluate the sustainability of a user weight-reduction policy in the analysis process of the user weight-reduction policy, so as to prevent the user from continuously adopting unreasonable weight-reduction measures to damage the health of the user without self knowledge.
Specifically, the method is applied to any server, the server is communicated with the electronic scale, the multi-frequency bioelectrical impedance data set, the sole state data set and the user basic information provided by the electronic scale are acquired and analyzed, the multi-dimensional physiological data capable of comprehensively reflecting the weight reduction state of the user is determined, the problems that the bioelectrical impedance data obtained by the existing bioelectrical impedance analysis technology applied to the electronic scale are low in accuracy and easily affected by external factors are solved, the scientificity and the comprehensiveness of the weight reduction strategy evaluation of the user are remarkably improved, the health sustainability analysis is carried out on the weight reduction strategy of the user based on the multi-dimensional index change rate, the weight reduction state evaluation report is determined and output according to the sustainability of the weight reduction strategy and the multi-dimensional index change rate, the situation that the user is harmful to the body health of the user and is not self-known due to the adoption of the extreme weight reduction strategy is effectively avoided, and the accuracy of the weight reduction strategy analysis is improved. Reference may be made to the following examples for specific implementation.
Fig. 2 is a flowchart of a weight-reduction analysis method for an electronic scale based on AI intelligence according to an embodiment of the present application, where the method of the present embodiment may be applied to a server in the above scenario. As shown in fig. 2, the method includes:
s201, acquiring a multi-frequency bioelectrical impedance data set, a sole state data set and user basic information, and analyzing the multi-frequency bioelectrical impedance data set and the sole state data set based on the user basic information to determine multi-dimensional physiological data.
The multi-frequency bioelectrical impedance data set can be an impedance data set output after different frequency currents pass through a human body, and can be collected through an electrode plate arranged in the electronic scale.
The sole state data set may be a set of parameters of the sole of the user that may affect the accuracy of bioelectrical impedance data, such as sole temperature, sole wettability, etc.
The user base information may be a base physical parameter of the user itself, such as height, age, gender, etc.
The multidimensional physiological data may be several physiological data capable of reflecting the current user weight loss status from different dimensions, such as body fat rate, muscle mass, moisture content, and the like.
Specifically, when the basic weight monitoring function is completed, the built-in electrode plate of the electronic scale is utilized to conduct micro-current which cannot be perceived by a human body into the human body of the user through the sole of the user, and bioelectrical impedance data fed back by the electrode is acquired, namely bioelectrical impedance analysis technology, through the technology, more complex internal parameters of the human body can be acquired by the electronic scale, but the bioelectrical impedance analysis technology applied to the electronic scale in the prior art generally adopts single-band or dual-band (high-frequency and low-frequency) micro-current, so that the granularity of data is overlarge, the user population in different states is difficult to deal with, and the micro-current is extremely easy to be influenced by external factors, and is particularly influenced by the direct contact with the electrodes of the electronic scale, such as the user sole wettability is higher, so that the wetted skin can better conduct the electric impedance, the acquired bioelectrical impedance data is lower than the actual situation, and the bioelectrical impedance data acquired by the prior bioelectrical impedance analysis technology applied to the electronic scale is difficult to solve the problem that larger errors are generated due to the user sole state, and the acquired bioelectrical impedance data cannot represent the actual situation in the current body.
Therefore, in order to improve the accuracy of the bioelectrical impedance analysis technology applied to the electronic scale on the analysis of human body parameters, the multi-frequency bioelectrical impedance data set and the sole state data set are obtained, the basic body data of the user are combined, the multi-dimensional physiological data capable of mapping the current weight reduction state of the user is obtained through a mathematical analysis means, the accuracy of the data is ensured, and meanwhile, the comprehensiveness of the subsequent analysis of the weight reduction state of the user is improved.
S202, determining the change rate of the multidimensional index according to the multidimensional physiological data and the historical physiological data.
The multi-dimensional index rate of change may be a rate of change of each of the multi-dimensional physiological data as compared to a corresponding same type of data in the historical physiological data.
The historical physiological data can be multidimensional physiological data of a historical time period means, and the historical physiological data can be obtained through a preset physiological database for storing physiological data of different time points of a user.
Specifically, for the evaluation of the weight-reduction strategy of the user, besides ensuring the comprehensiveness of the weight-reduction strategy of the user through the multidimensional physiological data, comprehensive consideration needs to be made from a reasonable time dimension, namely the multidimensional physiological data of the user cannot be used as transient data for analysis, the transient data cannot be placed on a corresponding time axis of the weight-reduction process of the user, the scientificity of the evaluation process of the weight-reduction strategy of the user can be ensured by paying attention to the change amplitude of the multidimensional physiological data on the time axis, and therefore, the change rate of different physiological data is obtained by comparing each type of physiological data in the multidimensional physiological data with the corresponding type of data in the historical physiological data, and the change rate of the multidimensional index is obtained by construction, so that an indispensable important data basis is provided for the subsequent weight-reduction strategy analysis.
S203, carrying out health sustainability analysis on the current weight-reduction strategy of the user according to the multidimensional index change rate, and evaluating the sustainability of the weight-reduction strategy.
The user's current weight-reduction policy may be a series of weight-reduction actions that the user makes during a weight-reduction period of time for the purpose of weight reduction.
The health sustainability analysis can be an analysis process that evaluates whether a user's current weight-loss policy can continue without affecting his physical health.
The weight-loss policy sustainability may be an evaluation result describing whether the user's current weight-loss policy is sustainable.
Specifically, in the process of weight reduction, the user is influenced by the urgent weight reduction mind of the user or some bad external information, extreme weight reduction measures such as extreme diet, rapid dehydration and the like are adopted, and are effective in terms of the change of single-dimension weight data in a short period, but if the extreme weight reduction measures are continuously adopted, huge damage is caused to the physical health of the user, so that the evaluation of the weight reduction strategy of the user cannot measure whether the weight reduction strategy is effective or not from the change angle of the physical data of the user singly, and the health sustainability of the weight reduction strategy of the user is evaluated on the basis of the change rate of the multidimensional index by a scientific mathematical analysis means, so that the weight reduction strategy which does not influence the physical health of the user and can be continuously carried out is taken as an effective strategy, the user is helped to carry out scientific weight reduction, and the user is prevented from being damaged by the extreme weight reduction measures continuously adopted.
S204, determining and outputting a weight-reduction state evaluation report according to the sustainability of the weight-reduction strategy and the multi-dimensional index change rate.
The weight-loss status evaluation report may be an evaluation report for reflecting the weight-loss status of the user, including the weight-loss policy sustainability evaluation result and the user multi-dimensional index change rate.
Specifically, after the sustainability evaluation of the user weight-reduction strategy is completed, the sustainability evaluation result and the multidimensional index change rate are comprehensively counted through a data visualization technology to construct a weight-reduction state evaluation report, and the weight-reduction state evaluation report is provided for the user through a man-machine interaction device or a mobile intelligent device so as to be used for scientific weight-reduction reference by the user.
By means of the method provided by the embodiment, the multi-frequency bioelectrical impedance dataset, the sole state dataset and the user basic information are comprehensively analyzed, multi-dimensional physiological data capable of comprehensively reflecting the weight reduction state of the user are determined, the problems that the bioelectrical impedance data obtained by the bioelectrical impedance analysis technology applied to the electronic scale is low in accuracy and easily influenced by external factors are solved, scientificity and comprehensiveness of evaluation on the weight reduction strategy of the user are remarkably improved, health sustainability analysis is conducted on the weight reduction strategy of the user based on the multi-dimensional index change rate, and a weight reduction state evaluation report is determined and output according to the sustainability of the weight reduction strategy and the multi-dimensional index change rate, so that the situation that the user is harmful to the body health of the user and is not self-known due to the adoption of the extreme weight reduction strategy is effectively avoided, and the accuracy of analysis on the weight reduction strategy is improved.
In some embodiments, the multi-frequency bioelectrical impedance data set is divided into frequency bands according to a preset frequency band set, a plurality of bioelectrical impedance values corresponding to different frequency bands are determined, the plurality of bioelectrical impedance values are calibrated in a targeted mode according to the sole wettability, the sole temperature and the stratum corneum thickness based on the different frequency bands, the plurality of calibrated bioelectrical impedance values are determined, and the plurality of calibrated bioelectrical impedance values are analyzed based on user basic information to determine multi-dimensional physiological data.
The sole state dataset includes sole wetness, sole temperature, and stratum corneum thickness.
The foot sole wettability can be a mathematical quantitative value describing the current user foot sole wettability, and the foot sole wettability can be obtained through a humidity sensor arranged in the electronic scale.
The sole temperature can be the current sole temperature value of the user, and the sole temperature can be obtained through a temperature sensor arranged in the electronic scale.
The thickness of the stratum corneum can be the thickness value of the stratum corneum of the sole skin of the current user, and the thickness of the stratum corneum can be obtained through a miniature ultrasonic sensor arranged in the electronic scale.
The preset frequency band set can be a preset current frequency band set for dividing micro-current frequency, and can comprise low-frequency bands (100 Hz-1 kHz), medium-low-frequency bands (1 kHz-10 kHz), medium-frequency bands (10 kHz-50 kHz), medium-high-frequency bands (50 kHz-100 kHz), high-frequency bands (100 kHz-1 MHz) and other current frequency bands.
The bioelectrical impedance value may be a degree of obstruction to current flow exhibited by a human body when a microcurrent is applied to the body of a current user.
Specifically, the micro-currents with different fine frequency ranges can enhance the analysis precision of different human body data, for example, the low-frequency micro-currents can analyze the moisture content in the human body, the high-frequency micro-currents can accurately analyze the fat content of the human body, the multi-frequency bioelectrical impedance data corresponding to the multi-frequency-range micro-currents are comprehensively analyzed, and the in-vivo data of the user can be obtained more comprehensively and accurately. However, the micro-current in different frequency bands can also affect the sole state of the user, and is specifically shown that when the sole wettability of the user is higher, the obtained bioelectrical impedance value is lower than the actual condition, because the water provides more ion conduction channels, when the sole temperature of the user is higher, the ion mobility can be improved, the measured bioelectrical impedance is lower than the actual condition, and when the sole horny layer thickness of the user is larger, the measured bioelectrical impedance is higher than the actual condition because the horny layer increases the resistance.
Meanwhile, because the influences of the sole states of the current means in different frequency ranges are different, the low-frequency current is obviously influenced by the sole states, and the high-frequency current is less influenced by the sole states than the low-frequency current due to the strong penetrability. Therefore, on the basis of different frequency bands, the bioelectrical impedance value is accurately and pertinently calibrated by a mathematical analysis means according to the sole wettability, the sole temperature and the stratum corneum thickness, and the error between the obtained bioelectrical impedance value and the actual human body impedance value is reduced.
Furthermore, after the bioelectrical impedance value is calibrated, the complexity of the personal condition of the user is also required to be considered, otherwise, the users with different ages, heights and sexes can appear, and the measured bioelectrical impedance value is similar, so that the subsequently obtained multidimensional physiological data is approximate to the abnormal condition, and the bioelectrical impedance value after the calibration is analyzed by mathematical means on the basis of the basic information of the user, so that the multidimensional physiological data which accords with the actual condition of the current user can be obtained.
According to the method provided by the embodiment, based on different frequency bands, the bioelectrical impedance values corresponding to different frequency bands are calibrated according to the sole wettability, the sole temperature and the stratum corneum thickness, different influences of the bioelectrical impedance values measured under different frequency band currents from the sole states of the user are fully considered, the obtained bioelectrical impedance values are more in line with the actual impedance states in the user, the calibrated bioelectrical impedance values are analyzed based on user basic information, multidimensional physiological data are obtained, individual differences among different users are fully considered, and the scientificity of the multidimensional physiological data is improved.
In some embodiments, the frequency band influence coefficient corresponding to each frequency band is determined according to different frequency bands, and the calibrated bioelectrical impedance value corresponding to each frequency band is determined according to the sole wettability, the sole temperature and the stratum corneum thickness based on the frequency band influence coefficient, specifically the following formula (1):
(1)
Wherein,For the calibrated bioelectrical impedance value corresponding to the current frequency band,For the bioelectrical impedance value corresponding to the current frequency band,For the frequency band influence coefficient corresponding to the current frequency band,For the preset humidity influence coefficient,For the degree of wetness of the sole of the foot,For the preset thickness influence coefficient,For the thickness of the stratum corneum to be the same,In order to preset the temperature influence coefficient,Is the sole temperature.
The frequency band influence coefficients can be coefficient values for expressing the influence degree of different current frequency bands on the sole state, the frequency band influence coefficients can be obtained through fitting analysis of electronic scale experimental data, a series of frequency band influence coefficients obtained through fitting are input into a preset frequency band coefficient set for storing the frequency band influence coefficients corresponding to different frequency bands, and the frequency band influence coefficients corresponding to each frequency band are determined through frequency band matching according to different frequency bands.
The preset humidity influence coefficient can be a coefficient value for expressing the influence degree of the sole humidity on the bioelectrical impedance value, and can be obtained through fitting analysis of experimental data of the electronic scale.
The preset thickness influence coefficient can be a coefficient value for expressing the influence degree of the sole stratum corneum thickness on the bioelectrical impedance value, and can be obtained through fitting analysis of experimental data of an electronic scale.
The preset temperature influence coefficient can be a coefficient value for expressing the influence degree of the sole temperature on the bioelectrical impedance value, and can be obtained through fitting analysis of experimental data of the electronic scale.
Specifically, by the method in the formula (1)Describing the overall effect of plantar wetting on bioelectrical impedance values, whereinExpressing the nonlinear influence effect of the wetting degree of the sole on the bioelectrical impedance value byDescribing the overall effect of plantar stratum corneum thickness on bioelectrical impedance values, whereinReflects the effect of the thickness of the sole cuticle on the bioelectrical impedance value in a marginal decreasing way byDescribing the overall influence of the sole temperature on the bioelectrical impedance value, slowing down the influence of temperature change on the bioelectrical impedance by utilizing a logarithmic function, conforming to the nonlinear influence characteristic of the sole temperature of a human body on the bioelectrical impedance, and further adjusting the influence of the bioelectrical impedance values corresponding to different frequency bands on the sole state of the user through frequency band influence coefficients.
According to the method provided by the embodiment, the bioelectrical impedance value after calibration is obtained by means of the mathematical analysis means and according to the frequency band influence coefficient corresponding to each frequency band, the sole wettability, the sole temperature and the stratum corneum thickness and through the mathematical formula, the bioelectrical impedance value of each frequency band which is measured at present is calibrated in a targeted mode, errors caused by the influence of the sole state on bioelectrical impedance values of different frequency bands are effectively reduced, and the accuracy of the subsequent multidimensional physiological data obtained based on the analysis of the bioelectrical impedance value after calibration is improved.
In some embodiments, the bioelectrical impedance values corresponding to the highest frequency and the lowest frequency are respectively extracted according to the plurality of calibrated bioelectrical impedance values, a high-frequency impedance value and a low-frequency impedance value are determined, the plurality of calibrated bioelectrical impedance values are analyzed, an average impedance value is determined, the body fat of the user is determined according to the low-frequency impedance value, the average impedance value and the real-time weight based on the height, the age and the sex factors, the body height, the high-frequency impedance value and the average impedance value are analyzed, the body moisture content is determined, the body muscle content is determined according to the height, the body fat of the user and the average impedance value, and the real-time weight, the resting heart rate, the body fat of the user, the body moisture content and the body muscle content are used as multidimensional physiological data.
User base information includes height, real-time weight, resting heart rate, age, and sex factors.
The high-frequency impedance value may be a bioelectrical impedance value corresponding to a high-frequency band of the plurality of calibrated bioelectrical impedance values.
The low-frequency impedance value may be a bioelectrical impedance value corresponding to a low-frequency band of the plurality of calibrated bioelectrical impedance values.
The sex factor can be an influence factor of sex on the body fat rate calculation result, and the sex factor can be obtained by analyzing electronic scale experimental data of different users.
The body fat rate of the user may be the proportion of the current body fat of the user to the total body weight thereof.
The in-body moisture content may be the total amount of moisture in the current user's body.
The in-vivo muscle content may be the total amount of muscle in the current user's body.
The resting heart rate may be the number of beats per minute of the heart that the current user is in resting state (in a relaxed state undergoing exercise).
Specifically, as can be seen from the foregoing embodiment, the bioelectrical impedance values corresponding to the low-frequency current and the high-frequency current are different in mapping emphasis on the human body data, so that by extracting the high-frequency impedance values and the low-frequency impedance values in the bioelectrical impedance values after a plurality of calibrations, the pertinence of the subsequent analysis process is stronger, and meanwhile, the average impedance value is taken as the impedance data with general representativeness, based on the impedance data with three dimensions, by combining with the user basic information, the mathematical analysis means are utilized, the body fat rate, the body water content and the body muscle content of the user are accurately quantified respectively in different combination manners, and the physiological data with five dimensions of real-time weight, resting heart rate, the body fat rate, the body water content and the body muscle content of the user are taken as multidimensional physiological data, so that whether the current user weight-reducing strategy is healthy and sustainable can be reflected in all directions, if the current user real-time weight is fast, but the body fat rate is not obviously reduced, and meanwhile, the body water content of the current user can be demonstrated to be a short-term dehydrated weight-reducing strategy, the negative in terms, the body weight-reducing strategy has no adverse effect on the health and the current user weight is not obviously reduced, and the current user weight is not obviously reduced in a real-time scope.
According to the method provided by the embodiment, three representative bioelectrical impedance values of the low-frequency impedance value, the average impedance value and the high-frequency impedance value are utilized, the body fat rate, the in-vivo moisture content and the in-vivo muscle content of the user are respectively analyzed and quantified in different combination modes by combining the basic information of the user, the accuracy of in-vivo data analysis of the user is improved, and the real-time body weight, the resting heart rate, the body fat rate, the in-vivo moisture content and the in-vivo muscle content five-dimensional human data are used as multidimensional physiological data, so that the subsequent weight reduction strategy analysis based on the multidimensional physiological data can comprehensively reflect whether the current weight reduction strategy of the user is sustainable.
In some embodiments, based on height, age and sex factors, the user body fat rate is determined from the low frequency impedance value, the average impedance value and the real-time body weight, in particular the following equation (2):
(2)
Wherein,For the body fat rate of the user,For the height of the patient,For the value of the high-frequency impedance,For the preset high-frequency impact index,As the value of the average impedance, the value of the impedance,In order to preset the first impedance impact index,For the preset age-affecting factor,For the age of the patient,As the sex factor, the sex factor is used,Is real-time body weight.
The preset high-frequency influence index can be a quantitative index expressing the influence of the high-frequency impedance value on the user body fat rate evaluation process, and can be obtained by analyzing experimental data of the electronic scale.
The preset first impedance influence index may be a quantitative index expressing the influence of the average impedance value on the user body fat rate evaluation process, and may be obtained by analyzing experimental data of the electronic scale.
The preset age influence coefficient may be a quantized coefficient expressing the influence of the user age on the user body fat rate estimation process.
Specifically, the height is squared by equation (2), i.eDescribing a total volume characterization of the user's body, reflecting the overall configuration of the user's body, and byReflecting sensitivity of body fat rate to overall structure and high frequency conductivity characteristics byReflecting the positive correlation between bioelectrical impedance value and body fat rate (generally, the conductivity of fat is low), and regulating the influence degree of bioelectrical impedance value on body fat rate by using preset first impedance influence indexAnd uniformly adjusting the calculation results of the two parts so that the body fat rate calculation result accords with the age and sex state of the current user.
By means of the method provided by the embodiment, the user body fat rate is scientifically and precisely quantified according to the low-frequency impedance value, the average impedance value and the real-time weight by means of a mathematical analysis means on the basis of the height, the age and the sex factors and through a mathematical formula, the accuracy of the user body fat rate value is improved, and meanwhile, individual differences caused by the body size, the age and the sex of the user are fully considered, so that the calculated user body fat rate height accords with the actual situation of the user.
In some embodiments, the height, high frequency impedance value and average impedance value are analyzed to determine the in vivo moisture content, specifically the following equation (3):
(3)
Wherein,For the in vivo moisture content,For the preset low-frequency influence coefficient,For the height of the patient,Is a value of the impedance at a low frequency,For the preset low frequency impact index,In order to preset the impedance influence coefficient,As the value of the average impedance, the value of the impedance,Is a preset second impedance impact index.
The preset low-frequency influence coefficient can be a quantized coefficient expressing the influence of the low-frequency impedance value on the in-vivo moisture content evaluation process of the user, and can be obtained by analyzing experimental data of the electronic scale.
The preset low-frequency influence index can be a quantitative index expressing the influence of the low-frequency impedance value on the in-vivo moisture content evaluation process of the user, and can be obtained by analyzing experimental data of the electronic scale.
The preset impedance influence coefficient may be a quantized coefficient expressing the influence of the average impedance value on the evaluation process of the moisture content in the user body, and may be obtained by analyzing experimental data of the electronic scale.
The preset second impedance influence index may be a quantization index expressing an influence of the average impedance value on the in-vivo moisture content evaluation process of the user, and may be obtained by analyzing experimental data of the electronic scale.
Specifically, by the formula (2)Reflecting the sensitivity of the in vivo moisture content to the overall architecture and low frequency conductivity characteristics byThe inverse of the average impedance value is taken to reflect the negative correlation between the bioelectrical impedance value and the in-vivo moisture content (the in-vivo moisture content has higher conductivity), the influence degree of the bioelectrical impedance value on the in-vivo moisture content is regulated by utilizing a preset second impedance influence index, and then the influence degree of the calculation results of the two parts on the in-vivo moisture content is regulated respectively through a preset low-frequency influence coefficient and a preset impedance influence coefficient, so that the accuracy of the calculated in-vivo moisture content is improved.
By means of the method provided by the embodiment, the mathematical analysis means is utilized, the in-vivo moisture content of the current user is precisely quantified through a mathematical formula on the basis of the height, the high-frequency impedance value and the average impedance value, the scientificity of the in-vivo moisture content analysis process of the user is remarkably improved, and the accuracy of the subsequent weight reduction strategy analysis is further improved.
In some embodiments, the in vivo muscle content is determined from the height, the user body fat rate, and the average impedance value, specifically the following equation (4):
(4)
Wherein,For the in vivo muscle content,In order to preset the height influence coefficient,For the height of the patient,As the value of the average impedance, the value of the impedance,In order to preset the height influence index,In order to preset the body fat influence coefficient,For the body fat rate of the user,In order to preset the body fat impact index,Is a preset adjustment coefficient.
The preset average impedance influence coefficient can be a quantized coefficient expressing the influence of the average impedance value on the in-vivo muscle mass evaluation process, and can be obtained by fitting and analyzing experimental data of the electronic scale.
The preset average impedance influence index can be a quantitative index for expressing the influence of the average impedance value on the in-vivo muscle mass evaluation process, and can be obtained by fitting and analyzing experimental data of the electronic scale.
The preset body fat influence coefficient can be a quantized coefficient for expressing the influence of the current body fat rate of the user on the in-vivo muscle quantity evaluation process of the user, and can be obtained by fitting and analyzing experimental data of the electronic scale.
The preset body fat influence index can be a quantitative index for expressing the influence of the current body fat rate of the user on the in-vivo muscle quantity evaluation process of the user, and can be obtained by fitting and analyzing experimental data of the electronic scale.
The preset adjustment coefficient can be a quantization coefficient for reducing the muscle mass error in the complex, and can be obtained by fitting and analyzing experimental data of the electronic scale.
Specifically, by the formula (4)Reflecting the sensitivity of the muscle mass in the body to the overall structure and average conductivity characteristics and by presetting an average impedance influence indexNonlinear influence on in-vivo muscle content evaluation process by user ratio of current body fat rate to heightThe negative influence of body fat on muscle quantity is emphasized, namely, the larger the body fat content is, the smaller the corresponding muscle ratio is, and under the condition of fixed height, the possibility that the increase of body fat rate can obviously reduce the muscle content is reflected by the preset body fat influence indexAnd the influence degree of the calculation results corresponding to the two parts on the calculation results of the internal muscle content is uniformly adjusted through the preset average impedance influence coefficient and the preset body fat influence coefficient, and the error of the whole calculation result is reduced by combining with the preset adjustment coefficient, so that the matching degree of the obtained internal muscle content and the actual situation of a user is improved.
According to the mode provided by the embodiment, the mathematical analysis means is utilized, and according to the height, the body fat rate and the average impedance value of the user, the in-vivo muscle content of the user is precisely quantified through a mathematical formula, so that the scientific muscle content value which accords with the current in-vivo condition of the user is obtained, and the accuracy of the subsequent weight reduction strategy analysis process is further improved.
In some embodiments, the composite impact index is determined based on the rate of change of moisture and the rate of change of muscle, the sustainable index is determined based on the composite impact index, the rate of change of body weight, the rate of change of body fat, and the rate of change of heart rate, the sustainable index is compared to a predetermined ideal index range, it is determined whether the sustainable index is within the predetermined ideal index range, if the sustainable index is within the predetermined ideal index range, it is determined that the weight-loss strategy sustainability is sustainable, and if the sustainable index is not within the predetermined ideal index range, it is determined that the weight-loss strategy sustainability is not sustainable.
The multi-dimensional index change rate includes a body weight change rate, a body fat change rate, a heart rate change rate, a moisture change rate, and a muscle change rate.
The rate of change of weight may be the rate of change of the user's current real-time weight compared to the historical weight.
The body fat change rate may be a rate of change of a user's current body fat rate as compared to a historical body fat rate.
The heart rate variability may be the variability of the user's current resting heart rate compared to the historical resting heart rate.
The rate of change of moisture may be a rate of change of the user's current in-vivo moisture content as compared to the historical in-vivo moisture content.
The rate of muscle change may be the rate of change of the muscle mass in the user's current body as compared to the historical body.
The composite impact index may be a quantitative index that indicates how much the dual impact of in vivo moisture content and muscle mass changes affects the sustainability assessment of the weight loss strategy.
The sustainability index can be quantized data describing the sustainability of the current weight-reduction strategy of the user, and the larger the sustainability index is, the stronger the sustainability of the current weight-reduction strategy of the user is.
The preset ideal index range can be a range interval of sustainable indexes corresponding to a healthy and effective weight reduction strategy, and can be obtained by analyzing a scientific weight reduction strategy.
Specifically, in the analysis process of the sustainability of the weight-loss strategy of the user, although the weight is a direct measurement index of the weight loss, the short-term fluctuation of the weight is probably not reflected in real fat change, because the weight-loss is influenced by the fluctuation of water, food digestion and other factors of the body, the fat loss rather than the pure weight loss is a healthy weight-loss target, the body fat change is helpful for judging whether the weight loss is mainly caused by fat loss, the change of the resting heart rate can indicate the improvement of the metabolic state and exercise tolerance of the body, the water content and the muscle quantity jointly influence the metabolism and the whole health state, the lack of sufficient water and the muscle support can cause pressure on a body system, so that the sustainability of the weight loss is reduced, and therefore, the composite influence index reflecting the combined action of the water content and the muscle quantity is synthesized, the sustainable index reflecting the sustainability of the weight-loss strategy is scientifically quantized through mathematical analysis means, so that the sustainability of the current weight-loss strategy of the user is accurately reflected, and the sustainability of the current weight-loss strategy of the user is accurately judged whether the current weight-loss strategy of the user can be sustained or not is obtained through comparing the sustainable index with the preset ideal index range.
By means of the method provided by the embodiment, the weight change rate, the body fat change rate, the heart rate change rate and the composite influence index reflecting the combined action of the moisture content and the muscle mass are synthesized, the sustainable index reflecting the sustainability of the weight-reduction strategy is scientifically analyzed to accurately reflect the sustainability of the current weight-reduction strategy of the user, and whether the current weight-reduction strategy of the user is sustainable or not is accurately judged by comparing the sustainable index with a preset ideal index range, so that the user can know whether the currently used weight-reduction strategy is sustainable or not in time.
In some embodiments, the sustainable index is determined from the composite impact index, the rate of change of body weight, the rate of change of body fat, and the rate of change of heart rate, specifically equation (5) below:
(5)
Wherein,As a result of the sustainable index(s),In order to obtain the rate of change of body weight,In order to preset the ideal weight change rate,In order to obtain the rate of change of body fat,In order to preset the ideal body fat change rate,For the preset heart rate influencing factor,In order to be a rate of change of the heart rate,In order to compound the impact index of the light,In order to achieve a rate of change of moisture,Is the rate of change of muscle;
determining a composite impact index according to the moisture change rate and the muscle change rate, specifically the following formula (6):
(6)
Wherein,In order to compound the impact index of the light,In order to achieve a rate of change of moisture,In order to be a rate of change of the muscle,To preset the ideal moisture change rate.
The preset ideal weight change rate can be an average weight change rate under the healthy weight reduction measure, and the preset ideal weight change rate can be obtained by analyzing weight reduction data of healthy people.
The preset ideal body fat change rate can be the average body fat change rate under the healthy weight-reduction measure, and can be obtained by analyzing weight-reduction data of healthy people.
The preset heart rate influence coefficient can be the average resting heart rate change rate under the health weight reduction measure, and can be obtained by analyzing the weight reduction data of the health crowd.
The preset ideal moisture change rate can be the average in-vivo moisture change rate under the health weight-reduction measure, and the preset ideal moisture change rate can be obtained by analyzing weight-reduction data of healthy people.
Specifically, by the formula (5)Measuring the difference between the body weight change rate and the preset ideal body weight change rate, the form of the exponential function is such that when the body weight change rate approaches the preset ideal body weight change rate, the term approaches 1, indicating ideal conditions, the farther from ideal, the faster the index decreases, this design highlighting the necessity of achieving the ideal change rate and regarding excessive deviation as disadvantageous, byReflecting the absolute difference between the rate of change of body fat and the ideal rate of change of body fat, in the form of an absolute value of a term that encourages reduction of the rate of change error of body fat by, unlike the exponential function described above, reflecting the direct effect of the rate of change error of body fat on sustainabilityProcessing the influence of heart rate variation rate, which is close to 1 in the ideal case, and preset ideal heart rate deviation rate, on sustainability, and reducing the heart rate variation to 0 in the excessive (too large or too small) stateThe effect of the combined action of the moisture content change and the muscle mass change on sustainability is reflected to balance the contributions of the moisture content change and the muscle mass change in sustainability assessment.
Further, the function in equation (5) is calculated by equation (6)Performing expansion by hyperbolic cosine functionAmplifying the influence of deviation between the water change rate and the preset ideal water change rate on the sustainability, and when the deviation between the water change rate and the preset ideal water change rate is too large, rapidly increasing the deviation to show the non-ideal water change condition byReflecting the direct influence of the rate of change of the muscle mass on sustainability, whether the muscle mass is increasing or decreasing, the value of the term is significantly increased whenever the absolute change is large, representing a high degree of concern for the maintenance of the muscle mass, as good muscle maintenance is a necessary condition for long-term health and weight loss.
Through the mode that this embodiment provided, utilize mathematical analysis means, according to compound influence index, weight change rate, body fat change rate and heart rate change rate, carry out accurate quantization through mathematical formula to sustainable index, carry out clear expansion to compound influence index's quantization process through mathematical formula simultaneously, guarantee to user's the scientificity and the accuracy of subtracting heavy tactics sustainability analysis process.
Fig. 3 is a schematic structural diagram of an AI-intelligent-based weight-reduction analysis system for an electronic scale according to an embodiment of the present application, and as shown in fig. 3, the weight-reduction analysis system 300 for an electronic scale according to the present embodiment includes a multidimensional analysis module 301, a change analysis module 302, a sustainable analysis module 303 and a report output module 304.
The multidimensional analysis module 301 is configured to acquire a multi-frequency bioelectrical impedance dataset, a sole state dataset and user basic information, analyze the multi-frequency bioelectrical impedance dataset and the sole state dataset based on the user basic information, and determine multidimensional physiological data;
A change analysis module 302, configured to determine a change rate of the multidimensional index according to the multidimensional physiological data and the historical physiological data;
the sustainable analysis module 303 is configured to perform a health sustainability analysis on the current weight-reduction policy of the user according to the multi-dimensional index change rate, and evaluate the sustainability of the weight-reduction policy;
and the report output module 304 is configured to determine and output a weight-loss status assessment report according to the sustainability of the weight-loss policy and the multi-dimensional index change rate.
Optionally, the multidimensional analysis module 301 is specifically configured to:
According to a preset frequency band set, carrying out frequency band division on the multi-frequency bioelectrical impedance data set, and determining a plurality of bioelectrical impedance values corresponding to different frequency bands;
based on the different frequency bands, performing targeted calibration on a plurality of bioelectrical impedance values according to the sole wettability, the sole temperature and the stratum corneum thickness, and determining a plurality of calibrated bioelectrical impedance values;
And analyzing a plurality of calibrated bioelectrical impedance values based on the user basic information to determine multidimensional physiological data.
Optionally, the multidimensional analysis module 301 is configured to, based on the different frequency bands, perform targeted calibration on a plurality of bioelectrical impedance values according to the sole wettability, the sole temperature and the stratum corneum thickness, and determine a plurality of calibrated bioelectrical impedance values when:
Determining a frequency band influence coefficient corresponding to each frequency band according to the different frequency bands;
Based on the frequency band influence coefficient, determining the bioelectrical impedance value after calibration corresponding to each frequency band according to the sole wettability, the sole temperature and the stratum corneum thickness, wherein the bioelectrical impedance value after calibration is specifically represented by the following formula:
;
Wherein,For the calibrated bioelectrical impedance value corresponding to the current frequency band,For the bioelectrical impedance value corresponding to the current frequency band,For the frequency band influence coefficient corresponding to the current frequency band,For the preset humidity influence coefficient,For the degree of wetness of the sole of the foot,For the preset thickness influence coefficient,For the thickness of the stratum corneum to be the same,In order to preset the temperature influence coefficient,Is the sole temperature.
Optionally, the multidimensional analysis module 301 is specifically configured to, when analyzing a plurality of the calibrated bioelectrical impedance values based on the user base information, determine multidimensional physiological data:
Respectively extracting bioelectrical impedance values corresponding to the highest frequency and the lowest frequency according to a plurality of calibrated bioelectrical impedance values, and determining a high-frequency impedance value and a low-frequency impedance value;
Analyzing a plurality of the calibrated bioelectrical impedance values to determine an average impedance value;
Determining a user body fat rate from the low frequency impedance value, the average impedance value, and the real-time weight based on the height, the age, and the gender factor;
Analyzing the height, the high-frequency impedance value and the average impedance value to determine the in-vivo moisture content;
determining an in vivo muscle content from the height, the user body fat rate, and the average impedance value;
the real-time body weight, the resting heart rate, the user body fat rate, the in-vivo moisture content, and the in-vivo muscle content are taken as the multidimensional physiological data.
Optionally, the multidimensional analysis module 301 is specifically configured to, when analyzing a plurality of the calibrated bioelectrical impedance values based on the user base information, determine multidimensional physiological data:
Respectively extracting bioelectrical impedance values corresponding to the highest frequency and the lowest frequency according to a plurality of calibrated bioelectrical impedance values, and determining a high-frequency impedance value and a low-frequency impedance value;
Analyzing a plurality of the calibrated bioelectrical impedance values to determine an average impedance value;
Determining a user body fat rate from the low frequency impedance value, the average impedance value, and the real-time weight based on the height, the age, and the gender factor;
Analyzing the height, the high-frequency impedance value and the average impedance value to determine the in-vivo moisture content;
determining an in vivo muscle content from the height, the user body fat rate, and the average impedance value;
the real-time body weight, the resting heart rate, the user body fat rate, the in-vivo moisture content, and the in-vivo muscle content are taken as the multidimensional physiological data.
Optionally, the multidimensional analysis module 301 determines the body fat rate of the user based on the height, the age and the sex factor according to the low-frequency impedance value, the average impedance value and the real-time weight according to the following formula:
;
Wherein,For the body fat percentage of the user,For the height of the person in question,For the value of the high-frequency impedance,For the preset high-frequency impact index,As a result of the value of the average impedance,In order to preset the first impedance impact index,For the preset age-affecting factor,For the said age of the patient in question,In order to be able to use the said sex factor,For the real-time body weight.
Optionally, the multidimensional analysis module 301 analyzes the height, the high-frequency impedance value and the average impedance value to determine the moisture content in the body, specifically the following formula:
;
Wherein,For the in-vivo moisture content of the said body,For the preset low-frequency influence coefficient,For the height of the person in question,For the value of the low-frequency impedance,For the preset low frequency impact index,In order to preset the impedance influence coefficient,As a result of the value of the average impedance,Is a preset second impedance impact index.
Optionally, the multidimensional analysis module 301 determines the in-vivo muscle content according to the height, the body fat rate of the user and the average impedance value, specifically the following formula:
;
Wherein,For the in vivo muscle content of the subject,In order to preset the height influence coefficient,For the height of the person in question,As a result of the value of the average impedance,In order to preset the height influence index,In order to preset the body fat influence coefficient,For the body fat percentage of the user,In order to preset the body fat impact index,Is a preset adjustment coefficient.
Optionally, the sustainable analysis module 303 is specifically configured to:
determining a composite impact index from the rate of change of moisture and the rate of change of muscle;
determining a sustainable index from the composite impact index, the body weight change rate, the body fat change rate, and the heart rate change rate;
comparing the sustainable index with a preset ideal index range, and judging whether the sustainable index is in the preset ideal index range or not;
If the sustainable index is within the preset ideal index range, determining that the sustainability of the weight-reduction strategy is sustainable;
and if the sustainable index is not in the preset ideal index range, determining that the sustainability of the weight-reduction strategy is not sustainable.
Optionally, the sustainable analysis module 303 determines a sustainable index according to the composite impact index, the weight change rate, the body fat change rate, and the heart rate change rate, specifically the following formula:
;
Wherein,In order for the sustainable index to be a function of the above,For the rate of change of the body weight,In order to preset the ideal weight change rate,For the rate of change of body fat in question,In order to preset the ideal body fat change rate,For the preset heart rate influencing factor,For the rate of change of the heart rate,For the composite impact index to be described,In order to achieve the rate of change of the moisture,Is the rate of change of the muscle;
and determining a composite influence index according to the moisture change rate and the muscle change rate, wherein the composite influence index is specifically expressed by the following formula:
;
Wherein,For the composite impact index to be described,In order to achieve the rate of change of the moisture,For the rate of change of the muscle to be described,To preset the ideal moisture change rate.
The system of the present embodiment may be used to perform the method of any of the foregoing embodiments, and its implementation principle and technical effects are similar, and will not be described herein.