Weight reduction analysis method and system for electronic scale based on AI intelligence

Abstract

The invention relates to the technical field of weight reduction analysis, in particular to a weight reduction analysis method and system for an electronic scale based on AI intelligence. The method comprises the following steps: 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 multi-dimensional physiological data; determining a multi-dimensional index change rate according to the multi-dimensional physiological data and the historical physiological data; according to the multi-dimensional index change rate, performing health sustainability analysis on the current weight loss strategy of the user, and evaluating the sustainability of the weight loss 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 method, the health sustainability analysis is carried out on the user weight loss strategy, so that the situation that the body health of the user is damaged and the user does not know by himself due to the adoption of an extreme weight loss strategy is effectively avoided, and the accuracy of weight loss strategy analysis is improved.

Description

Technical Field

[0001] The present application relates to the technical field of weight loss analysis, and in particular to a weight loss analysis method and system for electronic scales based on AI intelligence. Background Art

[0002] As people pay more attention to and pursue healthy living, especially with the prevalence of obesity and its related diseases, people are paying more and more attention to weight management. People hope to control their weight within an ideal range through various weight loss programs and measures. Electronic scales can be used to conveniently monitor weight.

[0003] However, existing electronic scales still only perform the simple task of monitoring and outputting weight data. Users who adopt extreme weight loss measures are likely to obtain false positive feedback from the simple dimensional weight change data provided by the electronic scales, and then be affected by continuous unreasonable weight loss measures during the weight loss process and damage their own health. Summary of the invention

[0004] The present application provides an AI-based intelligent weight loss analysis method and system for electronic scales to solve the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a weight loss analysis method for an electronic scale based on AI intelligence, the method comprising: obtaining a multi-frequency bioelectrical impedance data set, a sole status data set and basic user information, and analyzing the multi-frequency bioelectrical impedance data set and the sole status data set based on the basic user information to determine multidimensional physiological data; determining a multidimensional indicator change rate based on the multidimensional physiological data and historical physiological data; performing a health sustainability analysis on the user's current weight loss strategy based on the multidimensional indicator change rate, and evaluating the sustainability of the weight loss strategy; determining and outputting a weight loss status assessment report based on the sustainability of the weight loss strategy and the multidimensional indicator change rate.

[0006] Through the above technical scheme, the multi-frequency bioimpedance data set, the sole status data set and the user's basic information are comprehensively analyzed to determine the multidimensional physiological data that can comprehensively reflect the user's weight loss status, and solve the problems of low accuracy and susceptibility to external factors of the bioimpedance data obtained by the existing bioimpedance impedance analysis technology applied to electronic scales. The scientificity and comprehensiveness of the evaluation of the user's weight loss strategy are significantly improved, and the health sustainability of the user's weight loss strategy is analyzed based on the multidimensional indicator change rate. According to the sustainability of the weight loss strategy and the multidimensional indicator change rate, the weight loss status evaluation report is determined and output, which effectively avoids the situation where users adopt extreme weight loss strategies to damage their own health without knowing it, and improves the accuracy of the weight loss strategy analysis.

[0007] Optionally, the sole status dataset includes sole wetness, sole temperature and stratum corneum thickness, and the multi-frequency bioimpedance dataset and the sole status dataset are analyzed based on the user basic information to determine multi-dimensional physiological data, including: dividing the multi-frequency bioimpedance dataset into frequency bands according to a preset frequency band set, and determining a number of bioimpedance values ​​corresponding to different frequency bands; based on the different frequency bands, performing targeted calibration on a number of the bioimpedance values ​​according to the sole wetness, the sole temperature and the stratum corneum thickness, and determining a number of calibrated bioimpedance values; based on the user basic information, analyzing a number of the calibrated bioimpedance values ​​to determine multi-dimensional physiological data.

[0008] Through the above technical scheme, based on different frequency bands, the bioelectrical impedance values ​​corresponding to different frequency bands are calibrated in a targeted manner according to the wetness of the soles of the feet, the temperature of the soles of the feet and the thickness of the stratum corneum. The different influences of the state of the soles of the users on the bioelectrical impedance values ​​measured under currents of different frequency bands are fully considered, so that the obtained bioelectrical impedance values ​​are more in line with the actual impedance state of the user's body. Based on the basic information of the user, the calibrated bioelectrical impedance values ​​are analyzed to obtain multi-dimensional physiological data, which fully considers the individual differences between different users and improves the scientific nature of the multi-dimensional physiological data.

[0009] Optionally, based on the different frequency bands, the bioelectrical impedance values ​​are calibrated in a targeted manner according to the wetness of the sole of the foot, the temperature of the sole of the foot and the thickness of the stratum corneum to determine a number of calibrated bioelectrical impedance values, including: 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 calibrated bioelectrical impedance value corresponding to each frequency band according to the wetness of the sole of the foot, the temperature of the sole of the foot and the thickness of the stratum corneum, specifically the following formula: ; in, is the calibrated bioelectrical impedance value corresponding to the current frequency band, is the bioelectrical impedance value corresponding to the current frequency band, is the frequency band influence coefficient corresponding to the current frequency band, To preset the humidity influence coefficient, is the wetness of the sole of the foot, is the preset thickness influence coefficient, is the stratum corneum thickness, is the preset temperature influence coefficient, is the sole temperature.

[0010] Through the above technical solution, mathematical analysis is used to perform targeted calibration on the bioimpedance values ​​corresponding to each frequency band currently measured, based on the frequency band influence coefficient corresponding to each frequency band, according to the wetness of the sole, the temperature of the sole and the thickness of the stratum corneum, through mathematical formulas, to obtain the calibrated bioimpedance values, which effectively reduces the errors caused by the influence of the sole state on the bioimpedance values ​​of different frequency bands, thereby improving the accuracy of the subsequent multi-dimensional physiological data obtained based on the analysis of the calibrated bioimpedance values.

[0011] Optionally, the user basic information includes height, real-time weight, resting heart rate, age and gender factors, and the analysis of several calibrated bioelectrical impedance values ​​based on the user basic information to determine multidimensional physiological data includes: according to several calibrated bioelectrical impedance values, respectively extracting the bioelectrical impedance values ​​corresponding to the highest frequency and the lowest frequency to determine the high-frequency impedance value and the low-frequency impedance value; analyzing several calibrated bioelectrical impedance values ​​to determine the average impedance value; based on the height, the age and the gender factors, determining the user's body fat percentage according to the low-frequency impedance value, the average impedance value and the real-time weight; analyzing the height, the high-frequency impedance value and the average impedance value to determine the water content in the body; determining the muscle content in the body according to the height, the user's body fat percentage and the average impedance value; using the real-time weight, the resting heart rate, the user's body fat percentage, the water content in the body and the muscle content in the body as the multidimensional physiological data.

[0012] Through the above technical solution, three representative bioelectrical impedance values, namely low-frequency impedance value, average impedance value and high-frequency impedance value, are used in combination with the user's basic information to analyze and quantify the user's body fat percentage, body water content and body muscle content through different combinations, thereby improving the accuracy of the user's body data analysis. The five dimensions of human body data, namely real-time weight, resting heart rate, user body fat percentage, body water content and body muscle content, are used as multidimensional physiological data, so that the subsequent weight loss strategy analysis based on the multidimensional physiological data can fully reflect whether the user's current weight loss strategy is sustainable.

[0013] Optionally, the determining of the user's body fat percentage based on the height, the age and the gender factor according to the low-frequency impedance value, the average impedance value and the real-time weight is specifically the following formula: ; in, is the body fat percentage of the user, is the height, is the high frequency impedance value, To preset the high frequency impact index, is the average impedance value, To preset the first impedance influence index, is the preset age influence coefficient, For the age stated, is the gender factor, is the real-time body weight.

[0014] Through the above technical solution, mathematical analysis methods are used, based on height, age and gender factors, and through mathematical formulas, the user's body fat percentage is scientifically and accurately quantified according to the low-frequency impedance value, average impedance value and real-time weight. While improving the accuracy of the user's body fat percentage, it fully considers the individual differences caused by the user's body shape, age and gender, so that the calculated user body fat percentage is highly consistent with the user's actual situation.

[0015] Optionally, the analyzing the height, the high-frequency impedance value and the average impedance value to determine the water content in the body is specifically the following formula: ; in, is the body water content, To preset the low frequency influence coefficient, is the height, is the low frequency impedance value, To preset the low frequency impact index, is the preset impedance influence coefficient, is the average impedance value, The second impedance influence index is preset.

[0016] Through the above technical solution, mathematical analysis methods are used to accurately quantify the current user's body water content based on height, high-frequency impedance value and average impedance value through mathematical formulas, which significantly improves the scientific nature of the user's body water content analysis process, thereby improving the accuracy of subsequent weight loss strategy analysis.

[0017] Optionally, the muscle content in the body is determined according to the height, the user's body fat percentage and the average impedance value, specifically by the following formula: ; in, is the muscle content in the body, is the preset height influence coefficient, is the height, is the average impedance value, To preset the height impact index, To preset the body fat influence coefficient, is the body fat percentage of the user, To preset the body fat impact index, is the preset adjustment factor.

[0018] Through the above technical solution, mathematical analysis methods are used to accurately quantify the user's muscle content through mathematical formulas based on height, user body fat percentage and average impedance value, so as to obtain a scientific value of muscle content that is consistent with the user's current body condition, and further improve the accuracy of subsequent weight loss strategy analysis process.

[0019] Optionally, the multidimensional indicator change rate includes weight change rate, body fat change rate, heart rate change rate, water change rate and muscle change rate, and the health sustainability analysis of the user's current weight loss strategy is performed based on the multidimensional indicator change rate to evaluate the sustainability of the weight loss strategy, including: determining a composite impact index based on the water change rate and the muscle change rate; determining a sustainability index based on the composite impact index, the weight change rate, the body fat change rate and the heart rate change rate; comparing the sustainability index with a preset ideal index range to determine whether the sustainability index is within the preset ideal index range; if the sustainability index is within the preset ideal index range, determining that the sustainability of the weight loss strategy is sustainable; if the sustainability index is not within the preset ideal index range, determining that the sustainability of the weight loss strategy is unsustainable.

[0020] Through the above technical scheme, the sustainable index reflecting the sustainability of the weight loss strategy is scientifically analyzed by comprehensively combining the weight change rate, body fat change rate, heart rate change rate and the composite impact index reflecting the combined effects of water content and muscle mass, so as to accurately reflect the sustainability of the user's current weight loss strategy. By comparing the sustainable index with the preset ideal index range, an accurate judgment on whether the user's current weight loss strategy is sustainable is obtained, which helps to promptly let users know whether their current weight loss strategy is sustainable.

[0021] Optionally, the sustainable index is determined 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: ; in, is the sustainability index, is the weight change rate, To preset the ideal weight change rate, is the body fat change rate, To preset the ideal body fat change rate, To preset the heart rate influence coefficient, is the heart rate change rate, is the composite impact index, is the moisture change rate, is the muscle change rate; and the composite impact index is determined according to the water change rate and the muscle change rate, which is specifically the following formula: ; in, is the composite impact index, is the moisture change rate, is the muscle change rate, To preset the ideal moisture change rate.

[0022] Through the above technical solution, mathematical analysis is used to accurately quantify the sustainability index based on the composite impact index, weight change rate, body fat change rate and heart rate change rate through mathematical formulas. At the same time, the quantification process of the composite impact index is clearly expanded through mathematical formulas to ensure the scientificity and accuracy of the sustainability analysis process of the user's weight loss strategy.

[0023] In a second aspect, the present application provides a weight loss analysis system for an electronic scale based on AI intelligence, the system comprising: A multi-dimensional analysis module, used to obtain a multi-frequency bioelectrical impedance data set, a foot sole status data set and basic user information, and analyze the multi-frequency bioelectrical impedance data set and the foot sole status data set based on the basic user information to determine multi-dimensional physiological data; A change analysis module, used to determine the change rate of the multidimensional index according to the multidimensional physiological data and the historical physiological data; A sustainability analysis module, used to perform health sustainability analysis on the user's current weight loss strategy based on the change rate of the multi-dimensional indicators, and evaluate the sustainability of the weight loss strategy; The report output module is used to determine and output a weight loss status assessment report based on the sustainability of the weight loss strategy and the rate of change of the multi-dimensional indicators. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0025] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flowchart of a weight loss analysis method for an electronic scale based on AI intelligence provided in one embodiment of the present application; Figure 3 A structural schematic diagram of a weight loss analysis system for electronic scales based on AI intelligence provided in one embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0028] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0029] Existing electronic scales still only perform the simple task of monitoring and outputting weight data. Users who adopt extreme weight loss measures are prone to obtain false positive feedback from the simple dimensional weight change data provided by the electronic scales, and then be affected by continuous unreasonable weight loss measures during the weight loss process and damage their own health.

[0030] Based on this, the present application provides a weight loss analysis method for electronic scales based on AI intelligence. Comprehensively analyze the multi-frequency bioimpedance data set, the sole status data set and the user's basic information to determine the multidimensional physiological data that can fully reflect the user's weight loss status, solve the problem that the bioimpedance data obtained by the existing bioimpedance analysis technology applied to electronic scales is low in accuracy and easily affected by external factors, significantly improve the scientificity and comprehensiveness of the evaluation of the user's weight loss strategy, and conduct a health sustainability analysis of the user's weight loss strategy based on the multidimensional indicator change rate. According to the sustainability of the weight loss strategy and the multidimensional indicator change rate, determine and output the weight loss status evaluation report, effectively avoid the situation where the user adopts an extreme weight loss strategy to damage his or her own health without knowing it, and improve the accuracy of the weight loss strategy analysis.

[0031] Figure 1 A schematic diagram of an application scenario provided for this application. In the process of analyzing the user's weight loss strategy, the method of this application is applied to accurately evaluate the sustainability of the user's weight loss strategy to prevent the user from continuing to adopt unreasonable weight loss measures to harm his or her health without knowing it.

[0032] Specifically, the method of the present application is applied to any server, which communicates with an electronic scale, and determines multidimensional physiological data that can fully reflect the user's weight loss status by acquiring and analyzing the multi-frequency bioimpedance data set, the sole status data set and the user's basic information provided by the electronic scale, so as to solve the problem that the bioimpedance data obtained by the existing bioimpedance analysis technology applied to the electronic scale is low in accuracy and is easily affected by external factors, and significantly improves the scientificity and comprehensiveness of the evaluation of the user's weight loss strategy, and based on the multidimensional indicator change rate, the health sustainability analysis of the user's weight loss strategy is performed, and the weight loss status evaluation report is determined and output according to the sustainability of the weight loss strategy and the multidimensional indicator change rate, so as to effectively avoid the situation where the user adopts an extreme weight loss strategy to damage his or her own health without knowing it, and improve the accuracy of the weight loss strategy analysis. The specific implementation method can refer to the following embodiments.

[0033] Figure 2 This is a flowchart of a weight loss analysis method for an electronic scale based on AI intelligence provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, obtaining a multi-frequency bioelectrical impedance data set, a sole state data set and basic user information, and analyzing the multi-frequency bioelectrical impedance data set and the sole state data set based on the basic user information to determine multi-dimensional physiological data.

[0034] The multi-frequency bioelectrical impedance data set may be an impedance data set output after currents of different frequencies pass through a human body. The multi-frequency bioelectrical impedance data set may be collected through electrodes built into an electronic scale.

[0035] The sole state data set may be a set of parameters of the user's sole that may affect the accuracy of the bioelectrical impedance data, such as sole temperature, sole wetness, and the like.

[0036] The basic user information may be the basic physical parameters of the user, such as height, age, gender, etc.

[0037] The multi-dimensional physiological data may be a number of physiological data that can reflect the current weight loss status of the user from different dimensions, such as body fat percentage, muscle mass, and water content.

[0038] Specifically, while completing the basic weight monitoring function, the built-in electrode sheet of the electronic scale is used to conduct microcurrents that are imperceptible to the human body through the soles of the user's feet into the user's body, and obtain bioelectrical impedance data fed back by the electrodes, namely bioelectrical impedance analysis technology. Through this technology, the electronic scale can obtain more complex internal parameters of the human body. However, the existing bioelectrical impedance analysis technology applied to electronic scales usually adopts single-band or dual-band (high-frequency and low-frequency) microcurrents, resulting in too large data granularity, which is difficult to cope with user groups in different states. In addition, since the microcurrent is easily affected by external factors, it is particularly directly affected by the state of the soles of the human body that is in direct contact with the electrodes of the electronic scale. For example, if the soles of the user's feet are more moist, the moist skin can better conduct current, resulting in the obtained bioelectrical impedance data being lower than the actual situation. The existing bioelectrical impedance analysis technology applied to electronic scales is difficult to solve the problem of large errors caused by the state of the soles of the user's feet, which in turn causes the obtained bioelectrical impedance data to be unable to represent the actual situation of the user's current body.

[0039] Therefore, in order to improve the accuracy of human body parameter analysis by bioelectrical impedance analysis technology applied to electronic scales, by acquiring multi-frequency bioelectrical impedance data sets and sole status data sets, and combining them with the user's basic body data, mathematical analysis methods are used to obtain multi-dimensional physiological data that can map the user's current weight loss status. While ensuring data accuracy, the comprehensiveness of subsequent analysis of the user's weight loss status is improved.

[0040] S202. Determine the change rate of the multidimensional index according to the multidimensional physiological data and the historical physiological data.

[0041] The multi-dimensional indicator change rate may be a change rate of each physiological data in the multi-dimensional physiological data compared with the corresponding data of the same type in the historical physiological data.

[0042] The historical physiological data may be multi-dimensional physiological data of a historical time period, and the historical physiological data may be obtained through a preset physiological database for storing the physiological data of the user at different time points.

[0043] Specifically, in addition to ensuring the comprehensiveness of the evaluation of the user's weight loss strategy through multi-dimensional physiological data, it is also necessary to make comprehensive considerations from a reasonable time dimension. That is, the user's multi-dimensional physiological data cannot be analyzed as a transient data, but it is necessary to place it on the time axis corresponding to the user's weight loss process, and pay attention to the change range of the multi-dimensional physiological data on the time axis. Only in this way can the scientific nature of the user's weight loss strategy evaluation process be guaranteed. Therefore, by comparing each type of physiological data in the multi-dimensional physiological data with the corresponding type of data in the historical physiological data, the change rate of different physiological data is obtained, and the change rate of the multi-dimensional indicator is constructed to provide an indispensable and important data basis for the subsequent weight loss strategy analysis.

[0044] S203. Conduct a health sustainability analysis on the user's current weight loss strategy based on the rate of change of the multi-dimensional indicators, and evaluate the sustainability of the weight loss strategy.

[0045] The user's current weight loss strategy may be a series of weight loss measures taken by the user within a weight loss period for the purpose of weight loss.

[0046] Health sustainability analysis can be the process of evaluating whether a user's current weight loss strategy can be sustained without affecting their physical health.

[0047] The sustainability of the weight loss strategy may be an evaluation result describing whether the user's current weight loss strategy is sustainable.

[0048] Specifically, during the weight loss process, users may adopt extreme weight loss measures, such as extreme dieting, rapid dehydration, etc., due to their own eagerness to lose weight or the influence of some negative external information. These extreme weight loss measures are "effective" in the short term from the perspective of changes in single-dimensional weight data, but if extreme weight loss measures are continued, it will cause great damage to the user's physical health. Therefore, the evaluation of user weight loss strategies cannot be measured from the perspective of changes in user physical data alone. Whether it is effective should be evaluated based on the rate of change of multi-dimensional indicators through scientific mathematical analysis. The health sustainability of user weight loss strategies should be evaluated. Weight loss strategies that do not affect the user's physical health and can be sustained will be regarded as effective strategies, which will help users lose weight scientifically and avoid users from continuing to use extreme weight loss measures to damage their own health without knowing it.

[0049] S204. Determine and output a weight loss status assessment report based on the sustainability of the weight loss strategy and the rate of change of multi-dimensional indicators.

[0050] The weight loss status assessment report may be an assessment report that includes the weight loss strategy sustainability assessment results and the user's multi-dimensional indicator change rate and is used to reflect the user's weight loss status.

[0051] Specifically, after completing the sustainability assessment of the user's weight loss strategy, the data visualization technology is used to comprehensively count the sustainability assessment results and the change rates of multi-dimensional indicators to construct a weight loss status assessment report. The weight loss status assessment report is then provided to the user through human-computer interaction devices or mobile smart devices for reference in scientific weight loss.

[0052] Through the method provided in this embodiment, a multi-frequency bioimpedance data set, a sole status data set and basic information of the user are comprehensively analyzed to determine the multidimensional physiological data that can comprehensively reflect the user's weight loss status, so as to solve the problems that the bioimpedance data obtained by the existing bioimpedance impedance analysis technology applied to electronic scales is of low accuracy and is easily affected by external factors. The scientificity and comprehensiveness of the evaluation of the user's weight loss strategy are significantly improved, and the health sustainability of the user's weight loss strategy is analyzed based on the change rate of the multidimensional indicators. According to the sustainability of the weight loss strategy and the change rate of the multidimensional indicators, the weight loss status evaluation report is determined and output, which effectively avoids the situation where the user adopts an extreme weight loss strategy to damage his or her own health without knowing it, and improves the accuracy of the weight loss strategy analysis.

[0053] In some embodiments, a multi-frequency bioimpedance data set is divided into frequency bands according to a preset frequency band set, and a number of bioimpedance impedance values ​​corresponding to different frequency bands are determined; based on different frequency bands, a number of bioimpedance impedance values ​​are targetedly calibrated according to the wetness of the sole of the foot, the temperature of the sole of the foot, and the thickness of the stratum corneum, to determine a number of calibrated bioimpedance values; based on the user's basic information, a number of calibrated bioimpedance impedance values ​​are analyzed to determine multidimensional physiological data.

[0054] The sole status dataset includes sole moisture, sole temperature, and stratum corneum thickness.

[0055] The wetness of the sole of the foot may be a mathematical quantitative value describing the wetness of the sole of the current user's foot, and the wetness of the sole of the foot may be obtained through a humidity sensor built into the electronic scale.

[0056] The sole temperature may be a current sole temperature value of the user's foot, and the sole temperature may be obtained through a temperature sensor built into the electronic scale.

[0057] The stratum corneum thickness may be a thickness value of the stratum corneum of the skin on the sole of the current user, and the stratum corneum thickness may be acquired through a micro ultrasonic sensor built into the electronic scale.

[0058] The preset frequency band set can be a preset current frequency band set for dividing the microcurrent frequency. The preset frequency band set can include current frequency bands such as low frequency band (100Hz-1kHz), medium-low frequency band (1kHz-10kHz), medium frequency band (10kHz-50kHz), medium-high frequency band (50kHz-100kHz) and high frequency band (100kHz-1MHz).

[0059] The bioelectrical impedance value may be the degree of resistance to electric current exhibited by the human body when microcurrent is applied to the user's body.

[0060] Specifically, microcurrents of different frequency bands can enhance the accuracy of analyzing different human body data. For example, low-frequency microcurrents can analyze the water content in the human body, and high-frequency microcurrents can accurately analyze the fat content in the human body. Comprehensive analysis of multi-frequency bioimpedance data corresponding to multi-frequency microcurrents can obtain more comprehensive and accurate data on the user's body. However, microcurrents of different frequency bands will also affect the state of the user's soles. Specifically, when the user's soles are more moist, the bioimpedance value obtained will be lower than the actual situation, because water provides more ion conduction channels. When the temperature of the user's soles is high, the ion mobility will be increased, and the measured bioimpedance will also be lower than the actual situation. When the thickness of the stratum corneum on the soles of the user's feet is thicker, the stratum corneum will increase the resistance, resulting in the measured bioimpedance being higher than the actual situation.

[0061] At the same time, due to the different effects of different frequency bands on the state of the soles of the feet, low-frequency currents are more significantly affected by the state of the soles of the feet, while high-frequency currents are less affected by the state of the soles of the feet due to their strong penetration. Therefore, it is necessary to accurately and specifically calibrate the bioelectrical impedance value based on different frequency bands, according to the moisture content, temperature and thickness of the soles of the feet, and through mathematical analysis to reduce the error between the obtained bioelectrical impedance value and the actual human body impedance value.

[0062] Furthermore, after calibrating the bioelectrical impedance value, the complexity of the user's personal situation also needs to be considered. Otherwise, users of different ages, heights and genders may have similar measured bioelectrical impedance values, but the subsequent multi-dimensional physiological data obtained is approximately unreasonable. The calibrated bioelectrical impedance value should be analyzed through mathematical means based on the user's basic information to obtain multi-dimensional physiological data that conforms to the current user's actual situation.

[0063] Through the method provided in this embodiment, based on different frequency bands, the bioelectrical impedance values ​​corresponding to different frequency bands are calibrated in a targeted manner according to the wetness of the soles of the feet, the temperature of the soles of the feet and the thickness of the stratum corneum, and the different influences of the state of the soles of the users on the bioelectrical impedance values ​​measured under currents of different frequency bands are fully considered, so that the obtained bioelectrical impedance values ​​are more consistent with the actual impedance state of the user's body, and based on the basic information of the user, the calibrated bioelectrical impedance values ​​are analyzed to obtain multi-dimensional physiological data, which fully considers the individual differences between different users and improves the scientific nature of the multi-dimensional physiological data.

[0064] In some embodiments, according to different frequency bands, a frequency band influence coefficient corresponding to each frequency band is determined; based on the frequency band influence coefficient, according to the wetness of the sole of the foot, the temperature of the sole of the foot and the thickness of the stratum corneum, the calibrated bioelectrical impedance value corresponding to each frequency band is determined, specifically, as follows: (1) in, is the calibrated bioelectrical impedance value corresponding to the current frequency band, is the bioelectrical impedance value corresponding to the current frequency band, is the frequency band influence coefficient corresponding to the current frequency band, To preset the humidity influence coefficient, is the wetness of the sole of the foot, is the preset thickness influence coefficient, is the stratum corneum thickness, is the preset temperature influence coefficient, The temperature of the soles of feet.

[0065] The frequency band influence coefficient may be a coefficient value that expresses the degree to which different current frequency bands are affected by the state of the sole of the foot. The frequency band influence coefficient may be obtained by fitting analysis of the electronic scale experimental data, and a series of frequency band influence coefficients obtained by fitting are input into a preset frequency band coefficient set for storing frequency band influence coefficients corresponding to different frequency bands. According to different frequency bands, the frequency band influence coefficient corresponding to each frequency band is determined through frequency band matching.

[0066] The preset humidity influence coefficient may be a coefficient value that expresses the degree of influence of sole wetness on the bioelectrical impedance value. The preset humidity influence coefficient may be obtained by fitting analysis of electronic scale experimental data.

[0067] The preset thickness influence coefficient may be a coefficient value that expresses the degree of influence of the thickness of the sole stratum corneum on the bioelectrical impedance value. The preset thickness influence coefficient may be obtained by fitting analysis of electronic scale experimental data.

[0068] The preset temperature influence coefficient may be a coefficient value that expresses the degree of influence of the sole temperature on the bioelectrical impedance value, and the preset temperature influence coefficient may be obtained by fitting analysis of the electronic scale experimental data.

[0069] Specifically, through formula (1) Describe the overall effect of sole wetness on the bioelectrical impedance value, where Express the nonlinear effect of sole wetness on bioelectrical impedance value; Describe the overall effect of the thickness of the stratum corneum on the bioelectrical impedance value, where This reflects that the thickness of the stratum corneum on the sole of the foot has a marginal decreasing effect on the bioelectrical impedance value; Describe the overall impact of sole temperature on the bioelectrical impedance value, and use a logarithmic function to slow down the impact of temperature changes on the bioelectrical impedance, which is in line with the nonlinear impact of human foot temperature on bioelectrical impedance. Then, through the frequency band influence coefficient, adjust the impact of the user's foot state on the corresponding bioelectrical impedance values ​​of different frequency bands.

[0070] Through the method provided in this embodiment, mathematical analysis is used to perform targeted calibration on the bioimpedance values ​​corresponding to each frequency band currently measured based on the frequency band influence coefficient corresponding to each frequency band, according to the wetness of the sole, the temperature of the sole and the thickness of the stratum corneum, through mathematical formulas, to obtain the calibrated bioimpedance values, thereby effectively reducing the errors caused by the influence of the sole state on the bioimpedance values ​​of different frequency bands, and improving the accuracy of the subsequent multi-dimensional physiological data obtained based on the analysis of the calibrated bioimpedance values.

[0071] In some embodiments, based on several calibrated bioimpedance values, the bioimpedance values ​​corresponding to the highest frequency and the lowest frequency are respectively extracted to determine the high-frequency impedance value and the low-frequency impedance value; several calibrated bioimpedance values ​​are analyzed to determine the average impedance value; based on height, age and gender factors, the user's body fat percentage is determined according to the low-frequency impedance value, the average impedance value and the real-time weight; the height, high-frequency impedance value and the average impedance value are analyzed to determine the water content in the body; the muscle content in the body is determined according to the height, the user's body fat percentage and the average impedance value; the real-time weight, resting heart rate, the user's body fat percentage, the water content in the body and the muscle content in the body are used as multidimensional physiological data.

[0072] User basic information includes height, real-time weight, resting heart rate, age and gender factors.

[0073] The high-frequency impedance value may be a bioimpedance value corresponding to a high-frequency frequency band among a number of calibrated bioimpedance values.

[0074] The low-frequency impedance value may be a bioimpedance value corresponding to a low-frequency band among a number of calibrated bioimpedance values.

[0075] The gender factor may be a factor that affects the calculation result of body fat percentage, and the gender factor may be obtained by analyzing the experimental data of electronic scales of users of different genders.

[0076] The user's body fat percentage may be the ratio of the current user's body fat to his or her total weight.

[0077] The body water content may be the total amount of water in the current user's body.

[0078] The body muscle content may be the total amount of muscle in the current user's body.

[0079] The resting heart rate may be the number of heart beats per minute of the current user in a resting state (a relaxed state after exercising).

[0080] Specifically, it can be seen from the above embodiments that the bioelectrical impedance values ​​corresponding to the low-frequency current and the high-frequency current have different mapping focuses on human body data. Therefore, by extracting the high-frequency impedance values ​​and the low-frequency impedance values ​​in the calibrated bioelectrical impedance values, the subsequent analysis process is more targeted. At the same time, the average impedance value is used as the impedance data with generally representative characteristics. Based on the impedance data of the above three dimensions, combined with the basic information of the user, mathematical analysis methods are used to accurately quantify the user's body fat rate, body water content and body muscle content through different combinations, and the real-time weight, resting heart rate, user body fat rate, body water content and body muscle content are respectively converted into real-time weight, resting heart rate, user body fat rate, body water content and body muscle content. The five dimensions of physiological data, namely, body mass and muscle content, are multidimensional physiological data, which can fully reflect whether the current user's weight loss strategy is healthy and sustainable. For example, if the current user's real-time weight loss is fast, but the body fat rate does not decrease significantly, and the water content in the body is low, it can be explained that the current user is adopting a short-term dehydration weight loss strategy, which has a negative impact on physical health and is unsustainable. For example, if the current user's real-time weight loss is not obvious, but the body fat rate decreases significantly, the muscle mass increases significantly, and the resting heart rate decreases smoothly within the allowable range, it can be explained that the current user is adopting a reasonable intermittent exercise weight loss strategy, which has no impact on health and is sustainable.

[0081] Through the method provided in this embodiment, three representative bioelectrical impedance values, namely low-frequency impedance value, average impedance value and high-frequency impedance value, are used in combination with the user's basic information to analyze and quantify the user's body fat percentage, body water content and body muscle content through different combinations, thereby improving the accuracy of the user's body data analysis. The human body data in five dimensions, namely real-time weight, resting heart rate, user body fat percentage, body water content and body muscle content, are used as multidimensional physiological data, so that the subsequent weight loss strategy analysis based on the multidimensional physiological data can fully reflect whether the user's current weight loss strategy is sustainable.

[0082] In some embodiments, based on height, age and gender factors, the user's body fat percentage is determined according to the low-frequency impedance value, the average impedance value and the real-time weight, specifically the following formula (2): (2) in, is the user's body fat percentage, for height, is the high frequency impedance value, To preset the high frequency impact index, is the average impedance value, To preset the first impedance influence index, is the preset age influence coefficient, For age, is the gender factor, Real-time weight.

[0083] The preset high-frequency influence index may be a quantitative index that expresses the influence of the high-frequency impedance value on the user's body fat percentage evaluation process. The preset high-frequency influence index may be obtained by analyzing electronic scale experimental data.

[0084] The preset first impedance influence index may be a quantitative index that expresses the influence of the average impedance value on the user's body fat percentage evaluation process. The preset first impedance influence index may be obtained by analyzing electronic scale experimental data.

[0085] The preset age influence coefficient may be a quantitative coefficient that expresses the influence of the user's age on the user's body fat percentage evaluation process.

[0086] Specifically, through the square of height in formula (2), that is, , describes the total volume representation of the user's body, reflecting the overall structure of the user's body, and through Reflects the sensitivity of body fat percentage to overall structure and high-frequency conductivity characteristics; It reflects the positive correlation between bioelectrical impedance value and body fat percentage (usually fat has low conductivity), and uses the preset first impedance influence index to adjust the influence of bioelectrical impedance value on body fat percentage; The calculation results of the above two parts are uniformly adjusted to make the body fat percentage calculation results consistent with the age and gender status of the current user.

[0087] Through the method provided in this embodiment, mathematical analysis methods are used to scientifically and accurately quantify the user's body fat percentage based on height, age and gender factors through mathematical formulas, according to low-frequency impedance values, average impedance values ​​and real-time weight. While improving the accuracy of the user's body fat percentage, it fully considers the individual differences caused by the user's body shape, age and gender, so that the calculated user body fat percentage is highly consistent with the user's actual situation.

[0088] In some embodiments, the body height, high frequency impedance value and average impedance value are analyzed to determine the body water content, specifically the following formula (3): (3) in, is the water content in the body, To preset the low frequency influence coefficient, for height, is the low frequency impedance value, To preset the low frequency impact index, is the preset impedance influence coefficient, is the average impedance value, The second impedance influence index is preset.

[0089] The preset low-frequency influence coefficient may be a quantitative coefficient that expresses the influence of the low-frequency impedance value on the water content evaluation process in the user's body. The preset low-frequency influence coefficient may be obtained by analyzing the electronic scale experimental data.

[0090] The preset low-frequency impact index may be a quantitative index that expresses the impact of the low-frequency impedance value on the water content evaluation process in the user's body. The preset low-frequency impact index may be obtained by analyzing electronic scale experimental data.

[0091] The preset impedance influence coefficient may be a quantitative coefficient that expresses the influence of the average impedance value on the water content evaluation process in the user's body, and the preset impedance influence coefficient may be obtained by analyzing the electronic scale experimental data.

[0092] The preset second impedance influence index may be a quantitative index that expresses the influence of the average impedance value on the water content evaluation process in the user's body. The preset second impedance influence index may be obtained by analyzing electronic scale experimental data.

[0093] Specifically, through formula (2) Reflects the sensitivity of body water content to overall structure and low-frequency conductivity characteristics; The reciprocal of the average impedance value is taken to reflect the negative correlation between the bioelectrical impedance value and the body water content (the electrical conductivity of body water is higher), and the preset second impedance influence index is used to adjust the influence of the bioelectrical impedance value on the body water content; and then the influence of the calculation results of the above two parts on the body water content is adjusted by respectively using the preset low-frequency influence coefficient and the preset impedance influence coefficient to improve the accuracy of the calculated body water content.

[0094] Through the method provided in this embodiment, mathematical analysis methods are used to accurately quantify the current user's body water content through mathematical formulas based on height, high-frequency impedance value and average impedance value, thereby significantly improving the scientific nature of the user's body water content analysis process, and thereby improving the accuracy of subsequent weight loss strategy analysis.

[0095] In some embodiments, the muscle content in the body is determined based on the height, the user's body fat percentage and the average impedance value, specifically the following formula (4): (4) in, The muscle content in the body, is the preset height influence coefficient, for height, is the average impedance value, To preset the height impact index, To preset the body fat influence coefficient, is the user's body fat percentage, To preset the body fat impact index, is the preset adjustment factor.

[0096] The preset average impedance influence coefficient may be a quantitative coefficient that expresses the influence of the average impedance value on the in vivo muscle mass assessment process. The preset average impedance influence coefficient may be obtained by fitting and analyzing the electronic scale experimental data.

[0097] The preset average impedance influence index may be a quantitative index that expresses the influence of the average impedance value on the in vivo muscle mass assessment process. The preset average impedance influence index may be obtained by fitting and analyzing the electronic scale experimental data.

[0098] The preset body fat influence coefficient may be a quantitative coefficient that expresses the influence of the user's current body fat rate on the muscle mass evaluation process in the user's body. The preset body fat influence coefficient may be obtained by fitting and analyzing the electronic scale experimental data.

[0099] The preset body fat impact index may be a quantitative index that expresses the impact of a user's current body fat percentage on the muscle mass assessment process in the user's body. The preset body fat impact index may be obtained by fitting and analyzing electronic scale experimental data.

[0100] The preset adjustment coefficient may be a quantitative coefficient used to reduce the error of the comprehensive in vivo muscle mass, and the preset adjustment coefficient may be obtained by fitting and analyzing the experimental data of the electronic scale.

[0101] Specifically, through formula (4) Reflects the sensitivity of muscle mass to overall structure and average conductivity characteristics, and reflects it through a preset average impedance impact index The nonlinear effect on the muscle content assessment process; the ratio of the user's current body fat percentage to height , emphasizing the negative impact of body fat on muscle mass, that is, the greater the body fat content, the smaller the corresponding muscle proportion will be. Under the condition of fixed height, the increase in body fat percentage will significantly reduce the possibility of muscle content, and it is reflected by the preset body fat impact index The nonlinear impact on the in vivo muscle content evaluation process; and the preset average impedance influence coefficient and the preset body fat influence coefficient are used to uniformly adjust the degree of influence of the corresponding calculation results of the above two parts on the in vivo muscle content calculation results, and combined with the preset adjustment coefficient, reduce the error of the overall calculation result and improve the matching degree between the obtained in vivo muscle content and the actual situation of the user.

[0102] Through the method provided in this embodiment, mathematical analysis methods are used to accurately quantify the user's body muscle content through mathematical formulas based on height, user body fat percentage and average impedance value, so as to obtain a scientific value of muscle content that is consistent with the user's current body condition, and further improve the accuracy of the subsequent weight loss strategy analysis process.

[0103] In some embodiments, a composite impact index is determined based on the water change rate and the muscle change rate; a sustainable index is determined based on the composite impact index, the weight change rate, the body fat change rate and the heart rate change rate; the sustainable index is compared with a preset ideal index range to determine whether the sustainable index is within the preset ideal index range; if the sustainable index is within the preset ideal index range, the sustainability of the weight loss strategy is determined to be sustainable; if the sustainable index is not within the preset ideal index range, the sustainability of the weight loss strategy is determined to be unsustainable.

[0104] The change rates of multidimensional indicators include weight change rate, body fat change rate, heart rate change rate, water change rate and muscle change rate.

[0105] The weight change rate may be the change rate of the user's current real-time weight compared to the historical weight.

[0106] The body fat change rate may be the change rate of the user's current body fat rate compared to the historical body fat rate.

[0107] The heart rate change rate may be a change rate of the user's current resting heart rate compared to the user's historical resting heart rate.

[0108] The water content change rate may be a change rate of the user's current body water content compared to the user's historical body water content.

[0109] The muscle change rate may be a rate of change of the user's current body muscle mass compared to the user's historical body muscle mass.

[0110] The composite impact index can be a quantitative index that represents the degree of influence of the dual effects of changes in body water content and muscle mass on the sustainability assessment of weight loss strategies.

[0111] The sustainability index may be quantitative data that describes the sustainability of the user's current weight loss strategy. The larger the sustainability index is, the more sustainable the user's current weight loss strategy is.

[0112] The preset ideal index range may be a range interval of a sustainable index corresponding to a healthy and effective weight loss strategy, and the preset ideal index range may be obtained by analyzing a scientific weight loss strategy.

[0113] Specifically, in the process of analyzing the sustainability of the user's weight loss strategy, although body weight is a direct measure of weight loss, its short-term fluctuations may not reflect the actual changes in fat because it can be affected by water fluctuations, food digestion and other body factors; reducing fat rather than simply losing weight is the goal of healthy weight loss, and changes in body fat can help determine whether weight loss is mainly caused by fat reduction; changes in resting heart rate can indicate the body's metabolic state and improved exercise endurance; water content and muscle mass jointly affect metabolism and overall health, and lack of adequate water and muscle support will cause stress on the body's system, thereby reducing the durability of weight loss; therefore, the comprehensive weight change rate, body fat change rate, heart rate change rate and the composite impact index reflecting the combined effects of water content and muscle mass are used to scientifically quantify the sustainability index reflecting the sustainability of the weight loss strategy through mathematical analysis, so as to accurately reflect the sustainability of the user's current weight loss strategy, and by comparing the sustainability index with the preset ideal index range, an accurate judgment on whether the user's current weight loss strategy is sustainable is obtained.

[0114] Through the method provided in this embodiment, the sustainable index reflecting the sustainability of the weight loss strategy is scientifically analyzed by comprehensively analyzing the weight change rate, body fat change rate, heart rate change rate and the composite influence index reflecting the combined effects of water content and muscle mass, so as to accurately reflect the sustainability of the user's current weight loss strategy. By comparing the sustainable index with the preset ideal index range, an accurate judgment on whether the user's current weight loss strategy is sustainable is obtained, which helps to promptly let users know whether their current weight loss strategy is sustainable.

[0115] In some embodiments, the sustainable index is determined based on the composite impact index, the weight change rate, the body fat change rate and the heart rate change rate, specifically the following formula (5): (5) in, is the sustainability index, is the weight change rate, To preset the ideal weight change rate, is the body fat change rate, To preset the ideal body fat change rate, To preset the heart rate influence coefficient, is the heart rate change rate, is the composite impact index, is the moisture change rate, is the muscle change rate; The composite impact index is determined based on the water change rate and muscle change rate, which is specifically the following formula (6): (6) in, is the composite impact index, is the moisture change rate, is the muscle change rate, To preset the ideal moisture change rate.

[0116] The preset ideal weight change rate may be an average weight change rate under healthy weight loss measures, and the preset ideal weight change rate may be obtained by analyzing weight loss data of healthy people.

[0117] The preset ideal body fat change rate may be an average body fat change rate under healthy weight loss measures, and the preset ideal body fat change rate may be obtained by analyzing weight loss data of healthy people.

[0118] The preset heart rate impact coefficient may be the average resting heart rate change rate under healthy weight loss measures, and the preset heart rate impact coefficient may be obtained by analyzing weight loss data of healthy people.

[0119] The preset ideal water content change rate may be an average body water content change rate under healthy weight loss measures, and the preset ideal water content change rate may be obtained by analyzing weight loss data of healthy people.

[0120] Specifically, through formula (5) Measures the difference between the weight change rate and the preset ideal weight change rate. The exponential function is in the form of an exponential function, which is close to 1 when the weight change rate is close to the preset ideal weight change rate, indicating an ideal situation. The further away from the ideal, the faster the index decreases. This design highlights the necessity of achieving an ideal change rate and regards excessive deviations as disadvantages. Reflects the absolute difference between the body fat change rate and the ideal body fat change rate. Unlike the above exponential function, this term reflects the direct impact of the body fat change rate error on sustainability in the form of the absolute value of the term. This term encourages reducing the body fat change rate error; Processing the impact of the deviation between the heart rate change rate and the preset ideal heart rate on sustainability. When the heart rate change is ideal, this item is close to 1, while the heart rate change is excessive (too large or too small) and is reduced to 0; Reflects the combined impact of changes in water content and muscle mass on sustainability, and is used to balance the contributions of changes in water content and muscle mass in sustainability assessment.

[0121] Furthermore, the function in formula (5) is Expand it through the hyperbolic cosine function , amplifying the impact of the deviation between the moisture change rate and the preset ideal moisture change rate on sustainability. When the moisture change rate deviates too much from the preset ideal moisture change rate, this item will increase rapidly to highlight the unsatisfactory moisture change. Reflects the direct impact of the rate of change of muscle mass on sustainability. Regardless of whether muscle mass increases or decreases, as long as the absolute change is large, the value of this item will be significantly increased, reflecting the high attention paid to muscle mass maintenance, because good muscle maintenance is a necessary condition for long-term health and weight loss.

[0122] Through the method provided in this embodiment, mathematical analysis is used to accurately quantify the sustainability index based on the composite impact index, weight change rate, body fat change rate and heart rate change rate through mathematical formulas. At the same time, the quantification process of the composite impact index is clearly unfolded through mathematical formulas to ensure the scientificity and accuracy of the sustainability analysis process of the user's weight loss strategy.

[0123] Figure 3 A structural diagram of a weight loss analysis system for an electronic scale based on AI intelligence provided in one embodiment of the present application is shown in FIG. Figure 3 As shown, the weight loss analysis system 300 for an electronic scale of this embodiment includes: a multidimensional analysis module 301 , a change analysis module 302 , a sustainable analysis module 303 and a report output module 304 .

[0124] The multi-dimensional analysis module 301 is used to obtain a multi-frequency bioelectrical impedance data set, a foot sole state data set and basic user information, and analyze the multi-frequency bioelectrical impedance data set and the foot sole state data set based on the basic user information to determine multi-dimensional physiological data; A change analysis module 302, for determining a change rate of a multidimensional index based on the multidimensional physiological data and the historical physiological data; A sustainability analysis module 303 is used to perform health sustainability analysis on the user's current weight loss strategy according to the multi-dimensional indicator change rate, and evaluate the sustainability of the weight loss strategy; The report output module 304 is used to determine and output a weight loss status assessment report based on the sustainability of the weight loss strategy and the rate of change of the multi-dimensional indicators.

[0125] Optionally, the multidimensional analysis module 301 is specifically used to: According to a preset frequency band set, the multi-frequency bioelectrical impedance data set is divided into frequency bands to determine a number of bioelectrical impedance values ​​corresponding to different frequency bands; Based on the different frequency bands, according to the wetness of the sole of the foot, the temperature of the sole of the foot and the thickness of the stratum corneum, a plurality of the bioelectrical impedance values ​​are calibrated in a targeted manner to determine a plurality of calibrated bioelectrical impedance values; Based on the user basic information, a number of the calibrated bioelectrical impedance values ​​are analyzed to determine multi-dimensional physiological data.

[0126] Optionally, the multidimensional analysis module 301 performs targeted calibration on a plurality of the bioelectrical impedance values ​​based on the different frequency bands, according to the sole wetness, the sole temperature and the stratum corneum thickness, and determines a plurality of calibrated bioelectrical impedance values, specifically for: According to the different frequency bands, determining a frequency band influence coefficient corresponding to each frequency band; Based on the frequency band influence coefficient, according to the sole wetness, the sole temperature and the stratum corneum thickness, the calibrated bioelectrical impedance value corresponding to each frequency band is determined, specifically as follows: ; in, is the calibrated bioelectrical impedance value corresponding to the current frequency band, is the bioelectrical impedance value corresponding to the current frequency band, is the frequency band influence coefficient corresponding to the current frequency band, To preset the humidity influence coefficient, is the wetness of the sole of the foot, is the preset thickness influence coefficient, is the stratum corneum thickness, is the preset temperature influence coefficient, is the sole temperature.

[0127] Optionally, when the multidimensional analysis module 301 analyzes the calibrated bioelectrical impedance values ​​based on the user basic information to determine the multidimensional physiological data, it is specifically used to: According to the calibrated bioelectrical impedance values, respectively extracting the bioelectrical impedance values ​​corresponding to the highest frequency and the lowest frequency, and determining the high-frequency impedance value and the low-frequency impedance value; analyzing a plurality of the calibrated bioelectrical impedance values ​​to determine an average impedance value; Based on the height, the age and the gender factor, the user's body fat percentage is determined according to the low-frequency impedance value, the average impedance value and the real-time weight; Analyze the height, the high-frequency impedance value and the average impedance value to determine the water content in the body; Determining the muscle content in the body according to the height, the user's body fat percentage and the average impedance value; The real-time body weight, the resting heart rate, the user's body fat percentage, the body water content and the body muscle content are used as the multi-dimensional physiological data.

[0128] Optionally, when the multidimensional analysis module 301 analyzes the calibrated bioelectrical impedance values ​​based on the user basic information to determine the multidimensional physiological data, it is specifically used to: According to the calibrated bioelectrical impedance values, respectively extracting the bioelectrical impedance values ​​corresponding to the highest frequency and the lowest frequency, and determining the high-frequency impedance value and the low-frequency impedance value; analyzing a plurality of the calibrated bioelectrical impedance values ​​to determine an average impedance value; Based on the height, the age and the gender factor, the user's body fat percentage is determined according to the low-frequency impedance value, the average impedance value and the real-time weight; Analyze the height, the high-frequency impedance value and the average impedance value to determine the water content in the body; Determining the muscle content in the body according to the height, the user's body fat percentage and the average impedance value; The real-time body weight, the resting heart rate, the user's body fat percentage, the body water content and the body muscle content are used as the multi-dimensional physiological data.

[0129] Optionally, when the multidimensional analysis module 301 determines the user's body fat percentage based on the height, the age and the gender factor, according to the low-frequency impedance value, the average impedance value and the real-time weight, the formula is specifically as follows: ; in, is the body fat percentage of the user, is the height, is the high frequency impedance value, To preset the high frequency impact index, is the average impedance value, To preset the first impedance influence index, is the preset age influence coefficient, For the age stated, is the gender factor, is the real-time body weight.

[0130] Optionally, the multidimensional analysis module 301 determines the body water content by analyzing the height, the high-frequency impedance value and the average impedance value, specifically by the following formula: ; in, is the body water content, To preset the low frequency influence coefficient, is the height, is the low frequency impedance value, To preset the low frequency impact index, is the preset impedance influence coefficient, is the average impedance value, The second impedance influence index is preset.

[0131] Optionally, the multidimensional analysis module 301 determines the muscle content in the body according to the height, the user's body fat percentage and the average impedance value, specifically the following formula: ; in, is the muscle content in the body, is the preset height influence coefficient, is the height, is the average impedance value, To preset the height impact index, To preset the body fat influence coefficient, is the body fat percentage of the user, To preset the body fat impact index, is the preset adjustment factor.

[0132] Optionally, the sustainable analysis module 303 is specifically used for: Determining a composite impact index according to the water change rate and the muscle change rate; 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; Comparing the sustainable index with a preset ideal index range to determine whether the sustainable index is within the preset ideal index range; If the sustainability index is within the preset ideal index range, determining that the sustainability of the weight loss strategy is sustainable; If the sustainability index is not within the preset ideal index range, the sustainability of the weight loss strategy is determined to be unsustainable.

[0133] Optionally, when the sustainable analysis module 303 determines the sustainable index according to the composite impact index, the weight change rate, the body fat change rate and the heart rate change rate, it is specifically the following formula: ; in, is the sustainability index, is the weight change rate, To preset the ideal weight change rate, is the body fat change rate, To preset the ideal body fat change rate, To preset the heart rate influence coefficient, is the heart rate change rate, is the composite impact index, is the moisture change rate, is the muscle change rate; The composite impact index is determined according to the water change rate and the muscle change rate, specifically the following formula: ; in, is the composite impact index, is the moisture change rate, is the muscle change rate, To preset the ideal moisture change rate.

[0134] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A weight loss analysis method for electronic scales based on AI intelligence, characterized in that: include: Acquire a multi-frequency bioelectrical impedance data set, a sole state data set and basic user information, and analyze the multi-frequency bioelectrical impedance data set and the sole state data set based on the basic user information to determine multi-dimensional physiological data; Determining a multidimensional index change rate based on the multidimensional physiological data and the historical physiological data; Conduct health sustainability analysis on the user's current weight loss strategy based on the change rate of the multi-dimensional indicators to evaluate the sustainability of the weight loss strategy; According to the sustainability of the weight loss strategy and the rate of change of the multi-dimensional indicators, a weight loss status assessment report is determined and output.

2. The method according to claim 1, characterized in that The foot sole status data set includes foot sole moisture, foot sole temperature and stratum corneum thickness. The multi-frequency bioelectrical impedance data set and the foot sole status data set are analyzed based on the user basic information to determine multi-dimensional physiological data, including: According to a preset frequency band set, the multi-frequency bioelectrical impedance data set is divided into frequency bands to determine a number of bioelectrical impedance values ​​corresponding to different frequency bands; Based on the different frequency bands, according to the wetness of the sole of the foot, the temperature of the sole of the foot and the thickness of the stratum corneum, a plurality of the bioelectrical impedance values ​​are calibrated in a targeted manner to determine a plurality of calibrated bioelectrical impedance values; Based on the user basic information, a number of the calibrated bioelectrical impedance values ​​are analyzed to determine multi-dimensional physiological data.

3. The method according to claim 2, characterized in that Based on the different frequency bands, the plurality of bioelectrical impedance values ​​are calibrated in a targeted manner according to the sole wetness, the sole temperature and the stratum corneum thickness, and a plurality of calibrated bioelectrical impedance values ​​are determined, including: According to the different frequency bands, determining a frequency band influence coefficient corresponding to each frequency band; Based on the frequency band influence coefficient, according to the sole wetness, the sole temperature and the stratum corneum thickness, the calibrated bioelectrical impedance value corresponding to each frequency band is determined, specifically as follows: ； in, is the calibrated bioelectrical impedance value corresponding to the current frequency band, is the bioelectrical impedance value corresponding to the current frequency band, is the frequency band influence coefficient corresponding to the current frequency band, To preset the humidity influence coefficient, is the wetness of the sole of the foot, is the preset thickness influence coefficient, is the stratum corneum thickness, is the preset temperature influence coefficient, is the sole temperature.

4. The method according to claim 2, characterized in that: The user basic information includes height, real-time weight, resting heart rate, age and gender factors. Based on the user basic information, the plurality of calibrated bioelectrical impedance values ​​are analyzed to determine multi-dimensional physiological data, including: According to the calibrated bioelectrical impedance values, respectively extracting the bioelectrical impedance values ​​corresponding to the highest frequency and the lowest frequency, and determining the high-frequency impedance value and the low-frequency impedance value; analyzing a plurality of the calibrated bioelectrical impedance values ​​to determine an average impedance value; Based on the height, the age and the gender factor, the user's body fat percentage is determined according to the low-frequency impedance value, the average impedance value and the real-time weight; Analyze the height, the high-frequency impedance value and the average impedance value to determine the water content in the body; Determining the muscle content in the body according to the height, the user's body fat percentage and the average impedance value; The real-time body weight, the resting heart rate, the user's body fat percentage, the body water content and the body muscle content are used as the multi-dimensional physiological data.

5. The method according to claim 4, characterized in that The method of determining the user's body fat percentage based on the height, the age and the gender factor according to the low-frequency impedance value, the average impedance value and the real-time weight is specifically the following formula: ； in, is the body fat percentage of the user, The height, is the high frequency impedance value, To preset the high frequency impact index, is the average impedance value, To preset the first impedance influence index, is the preset age influence coefficient, For the age stated, is the gender factor, is the real-time body weight.

6. The method according to claim 4, characterized in that The analyzing the height, the high-frequency impedance value and the average impedance value to determine the water content in the body is specifically the following formula: ； in, is the body water content, To preset the low frequency influence coefficient, is the height, is the low frequency impedance value, To preset the low frequency impact index, is the preset impedance influence coefficient, is the average impedance value, The second impedance influence index is preset.

7. The method according to claim 4, characterized in that The muscle content in the body is determined according to the height, the user's body fat percentage and the average impedance value, specifically the following formula: ； in, is the muscle content in the body, is the preset height influence coefficient, is the height, is the average impedance value, To preset the height impact index, To preset the body fat influence coefficient, is the body fat percentage of the user, To preset the body fat impact index, is the preset adjustment factor.

8. The method according to claim 1, characterized in that: The multi-dimensional index change rate includes weight change rate, body fat change rate, heart rate change rate, water change rate and muscle change rate. The health sustainability analysis of the user's current weight loss strategy is performed based on the multi-dimensional index change rate to evaluate the sustainability of the weight loss strategy, including: Determining a composite impact index according to the water change rate and the muscle change rate; 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; Comparing the sustainable index with a preset ideal index range to determine whether the sustainable index is within the preset ideal index range; If the sustainability index is within the preset ideal index range, determining that the sustainability of the weight loss strategy is sustainable; If the sustainability index is not within the preset ideal index range, the sustainability of the weight loss strategy is determined to be unsustainable.

9. The method according to claim 8, characterized in that The sustainable index is determined 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: ； in, is the sustainability index, is the weight change rate, To preset the ideal weight change rate, is the body fat change rate, To preset the ideal body fat change rate, To preset the heart rate influence coefficient, is the heart rate change rate, is the composite impact index, is the moisture change rate, is the muscle change rate; The composite impact index is determined according to the water change rate and the muscle change rate, specifically the following formula: ； in, is the composite impact index, is the moisture change rate, is the muscle change rate, To preset the ideal moisture change rate.

10. A weight loss analysis system for electronic scales based on AI intelligence, characterized in that: include: A multi-dimensional analysis module, used to obtain a multi-frequency bioelectrical impedance data set, a foot sole status data set and basic user information, and analyze the multi-frequency bioelectrical impedance data set and the foot sole status data set based on the basic user information to determine multi-dimensional physiological data; A change analysis module, used to determine the change rate of the multidimensional index according to the multidimensional physiological data and the historical physiological data; A sustainability analysis module, used to perform health sustainability analysis on the user's current weight loss strategy based on the change rate of the multi-dimensional indicators, and evaluate the sustainability of the weight loss strategy; The report output module is used to determine and output a weight loss status assessment report based on the sustainability of the weight loss strategy and the rate of change of the multi-dimensional indicators.

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