WO2021080027A1

WO2021080027A1 - Healthcare system using smart scale

Info

Publication number: WO2021080027A1
Application number: PCT/KR2019/013889
Authority: WO
Inventors: 김광진; 김진서
Original assignee: 김광진; 김진서
Priority date: 2019-10-22
Filing date: 2019-10-22
Publication date: 2021-04-29
Also published as: KR102161384B1

Abstract

A healthcare system using a smart scale according to the present invention comprises: the smart scale capable of recognizing a bio-signal of a user and measuring body fat for each body part of the user; an electronic device which interworks with the smart scale and through which the user can identify a result value measured from the smart scale; and a server for exchanging data with the smart scale and the electronic device and storing records of the user's healthcare, wherein the server includes a recommendation mode for analyzing the user's current health state to propose a healthcare program to the user.

Description

Health care system using a smart scale

The present invention relates to a healthcare system for providing an appropriate health program by tracking and investigating the health history of a person using a smart scale, and in detail, the system searches for a similar history that is a subject of comparison with the personal history, which is the user's health management history. And, on the basis of the similar history, it relates to a health care system using a smart scale that recommends a diet diet, an exercise method, and the like for efficient health management to a user.

In the modern society, as dietary life is advanced, Western-type diseases such as obesity are gradually increasing. Accordingly, in various public facilities such as gymnasiums and hospitals, scales having various functions are being widely distributed so that one's health status can be checked. However, since analog scales are inconvenient to be inferior in precision, most institutions use digital scales using load cells.

In the conventional digital scale, when the user inputs his or her information, analysis information for health management is displayed, and data such as the user's information and body composition analysis results are stored in the server, enabling health history management for each individual. . Such data could be checked by users through electronic devices such as smartphones. Specifically, whenever a user uses a digital scale, the user can check the corresponding data by connecting his/her smartphone and the digital scale to each other through a method such as Bluetooth, and then importing his/her data. As such, in the related art, whenever a user wants to check his/her data through a smartphone, it is cumbersome to use the system because the scale and his/her smartphone have to be interlocked.

In addition, as disclosed in Korean Patent Registration No. 10-1950555, conventionally, an application capable of checking various diseases by managing user's weight information and measuring a bio-signal through a smartphone has been developed and released. However, such a conventional health management system using a smart phone simply checks the user's weight information or whether there is a disease, and has not been able to propose an active solution to solve this.

Therefore, for systematic health management, it was necessary to individually receive training while attending a health club, or to conduct separate management through diet and medical means. As a result, there is a problem that too much time and money are consumed for health care, and further, problems such as failure of continuous health management due to a decrease in the user's motivation after a certain period of time have occurred.

An object of the present invention is to enable a user to easily check data related to his or her health through a smartphone, and to search for similar histories to be compared based on the user's eating habits and activities, and to provide personalized health care services for each individual. It is to provide a healthcare system using a smart scale that can recommend.

The present invention provides the following technical means as a means for solving the above problems.

A health care system using a smart scale according to the present invention includes a smart scale capable of recognizing a user's bio-signal and measuring body fat by body part of the user, and a result value measured by the user from the smart scale linked to the smart scale. An electronic device capable of checking the information, and a server that exchanges data with the smart scale and the electronic device and stores a record of the user's health management, wherein the server analyzes the current health state of the user and provides a health management program to the user. Includes a recommended mode that suggests.

According to the present invention, in order for the user to use the system, it is sufficient to exchange data by interlocking the scale and his/her smartphone with a method such as Bluetooth only at the beginning of use, and when this initial registration is completed, it is no longer interlocked with Bluetooth, etc. Even without this, since the user can easily check the data measured by the weight scale and the data processed by the server through his/her smartphone, the convenience of use can be greatly improved.

In addition, according to the system, the user's self-history measured through the smart scale and the similar history to be compared are searched, and based on the similar history, recommendations for success cases, future diet diet, exercise amount, exercise method, etc. Since recommendations are made, there is an advantage in that efficient personalized health care can be achieved.

In addition, since each user's information stored in the server becomes basic health management data, and the data can be grafted with other solutions, there is an advantage in that the reliability of the system can be gradually improved as the usage of the system increases.

The accompanying drawings are for explaining the contents of the present invention in more detail to a person skilled in the art, and the technical idea of the present invention is not limited thereto.

1 is a block diagram showing the overall configuration of a healthcare system according to an embodiment of the present invention.

2 is a perspective view showing a smart scale of the healthcare system.

3 is a block diagram illustrating detailed functions of a server in the healthcare system.

4 is a flowchart illustrating a process of executing a similar history search mode and a recommendation mode among the functions of the server.

5 is a block diagram showing an example of execution of the recommendation mode.

6 is a flowchart illustrating a process of executing a compensation mode among the functions of the server.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, terms or words used in the present specification and claims should not be interpreted in a conventional or dictionary meaning, and the inventor shall appropriately define the concept of terms in order to describe his own invention in the best way. Based on the principle that it is possible, it should be interpreted as a meaning and concept consistent with the technical idea of the present invention.

Therefore, the embodiments described in the present specification and the configurations shown in the drawings are only the most preferred implementation of the present invention, and do not represent all the technical ideas of the present invention. It should be understood that there may be equivalents and variations.

1 is a block diagram showing the overall configuration of a healthcare system according to an embodiment of the present invention. And, Figure 2 is a perspective view showing a smart scale of the health care system.

1 and 2, the healthcare system according to the present invention is a smart scale 10 capable of measuring a user's weight, obesity, body fat, etc., and interlocking to exchange signals with the smart scale 10 It includes a smart phone (200). In addition, the information stored and inputted in the smart scale 10 and the smart phone 200 is transmitted to the server 100, and the server 100 analyzes and processes such information, and the smart scale 10 Alternatively, it may be transmitted to the smartphone 200. The smart phone 200 presents an example of an electronic device mainly used by a user, and a PDA capable of exchanging information with the smart scale 10 and the server 100 in place of the smart phone 200, Other electronic devices such as laptops may also be used.

The user's use of the healthcare system is as follows. First, after the user runs the application of the smart phone 200, the smart scale 10 and the smart phone 200 are linked to each other through a Bluetooth method. When the Bluetooth linkage between the two devices is completed, the user recognizes his or her own biometric signal through the smart scale 10. Accordingly, information on the bio-signal is transmitted to the smartphone 200. Then, the user inputs his/her personal information such as his/her age, height, and gender into the smart phone 200, and information about his/her personal information is transmitted to the smart scale 10. That is, information on the user's bio-signal and the user's personal information are shared with each of the smart scale 10 and the smartphone 200.

The user's biosignal measured through the smart scale 10 may be, for example, a user's foot. Specifically, when the user puts the soles of the feet on the stepping plate 20 of the smart scale 10, the foot is recognized among the user's bio-signals, and information about this may be input as the user's personal information.

As another example, as the biosignal, vein recognition that can determine the identity of the user using a vein flowing through the user's palm or finger may be used.In another example, light that recognizes the user by detecting a change in the user's optical blood volume through transmitted light. Volume pulse wave recognition may also be used.

However, in order to increase the recognition rate for the user, in the present invention, a method according to complex bio recognition in which two or more of the foot finger recognition, vein recognition, and optical volume pulse wave recognition are used together may be used. For example, the user's bio-signal measured through the smart scale 10 may be a composite bio-recognition using both vein recognition and foot finger recognition, or a composite bio-recognition day using both vein recognition and photovoltaic pulse wave recognition. Alternatively, it may be a composite biometric recognition in which both foot finger recognition and optical volume pulse wave recognition are used, or a composite bio recognition in which both foot finger recognition, vein recognition, and optical volume pulse wave recognition are used. As described above, the smartphone 200 may be Information on the bio-signals transmitted to and personal information input through the smartphone 200 are transmitted to the server 100 and converted into basic data. That is, the server 100 receives various types of information from the smartphone 200, converts it into basic data of the user, and stores it. Through this process, the initial registration of the user is completed (see Fig. 1(a)).

When the initial registration process is completed, after that, the user can utilize the healthcare system even if the smartphone 200 and the scale 10 are not interlocked with each other through a method such as Bluetooth.

Specifically, when the smart scale 10 is connected to an internet network 300 such as a router, the current body weight, obesity, body fat, etc. of the user measured by the smart scale 10 through the internet network 300 Information is transmitted to the server 100. The server 100 performs a process of processing the basic data of the user converted at the time of initial registration and information on the current body information together. This processed data is displayed to the user as information on his/her body information history when the user automatically logs in to the application of the smartphone 200 (see FIG. 1(b)).

As described above, according to the present invention, it is sufficient that the smart scale 10 and the smart phone 200 are linked in the Bluetooth method only at the beginning of use, and when the initial registration is completed, the user can Since the processed information can be checked through 200, the convenience of use can be greatly improved.

The smart scale 10 connects the handle 30 serving as a handle that the user can grasp, the stepping plate 20 serving as a footrest in contact with the user's foot, and the handle 30 and the stepping plate 20 It consists of a support (40).

The stepping plate 20 is provided with a total of four sensing units 25 that present a contact point with the user's sole, and similarly, a total of four sensing units presenting a contact point with the user's palm in the handle 30. A portion 35 is formed. These eight sensing

units

25 and 35 are electrodes that allow electricity to flow through the human body so that the user's body composition can be measured. A method in which the body composition of a user's human body can be analyzed through the

sensing units

25 and 35 through which electricity flows in this way is referred to as a touch electrode measurement method.

This touch-type electrode measurement method refers to a method of analyzing body composition by measuring a resistance value of how much electricity passes through when electricity is passed through a user's human body. In the present invention, among the touch-type electrode measurement methods, a direct impedance measurement method (DSM-BIA) for each part that can analyze body composition such as body fat for each part of the body is used.

The direct impedance measurement method for each part is a method of measuring the impedances of both arms, legs, and torso of the human body, respectively, and accurately analyzes the body composition of each part by separately measuring the impedances of both arms, legs, and torso of the human body having different density and cross-sectional area This is the way to do it.

As can be seen in Figure 2, the smart scale 10 according to the present invention uses an 8-point touch-type electrode method. As described above, as the 8-point touch electrode method is used, body composition such as body fat can be more accurately measured for each part, and reliability of the measurement result can be increased.

As another example, the smart scale 10 may use a four-point touch-type electrode method, which is a method that is widely used in the past. According to this four-point touch-type electrode method, the four sensing units 35 installed on the handle 30 may be excluded from the configuration shown in FIG. 2. That is, the body composition may be measured by measuring the body composition of the user's lower body through the four detection units 25 formed on the stepping plate 20 and estimating the body composition of the user's upper body based on the body composition of the corresponding lower body.

The user can check the measurement result through the monitor 50 formed on the central front portion of the handle 30. The monitor 50 is an LCD monitor, which displays the result of body composition analysis for each body part of the user. That is, the user can check the body composition analysis result in real time through the monitor 50.

In addition, in the present invention, a heart rate meter for measuring not only the user's body composition but also the user's heart rate state may be additionally installed. The heart rate monitor may be installed in the form of a sensor on the handle 30 of the smart scale 10, or may be configured as a wristwatch separately from the smart scale 10 as another example. The heart rate monitor is equipped with a heart rate sensor that measures a user's heart rate state. That is, through the heart rate sensor, the number of times the user's heart beats per minute may be checked and the corresponding value may be displayed on the monitor 50 or the display of a separate wristwatch. According to this process, the user's body composition and heart rate may be displayed. When the measurement of the condition is completed, the data is transmitted to the user's smartphone and the server to deliver information on the user's current health condition. Hereinafter, the smart scale 10 and the server 100 for exchanging information with the smart phone 200 will be described. 3 is a block diagram illustrating detailed functions of a server in the healthcare system.

Referring to FIG. 3, the server 100 tracks and manages the user's health history, and further analyzes and processes various information to provide a better health management service to the user and provides it to the user.

Specifically, when the user uses the smart scale 10 for a certain period of time, the self history measurement mode 110 of the server 100 is executed to store and edit information on the use history of the smart scale 10 . The hysteresis measurement mode 110 may exhibit its functions in various ways depending on the usage period and number of times of the smart scale 10.

If the user wants to use the smart scale 10 at a predetermined time, e.g., 1 day, every other day, a week, a specific day, etc., a periodic measurement mode among the hysteresis measurement modes 110 is activated. do. According to the periodic measurement mode, since the user regularly uses the smart scale 10, information on a more reliable usage history can be obtained, and an accurate analysis result can be derived accordingly. In this case, an alarm unit for notifying the user that a preset time has arrived may be additionally installed on the smart scale 10. Such an alarm unit may be a visual alarm or an audible alarm.

On the contrary, if the user sets only the whole body composition measurement period and wants to use the smart scale 10 randomly within the entire period, an irregular measurement mode among the hysteresis measurement modes 110 is activated. In the occasional measurement mode, a minimum number of times of use of the smart scale 10, measurement timing, etc. should be presented in order to perform accurate body composition analysis within a specific period. Such a periodic measurement mode or an irregular measurement mode may be selected by the user, or may be automatically set in the server 100 according to the user's use frequency of the smart scale 10.

When the hysteresis measurement mode 110 is terminated, the server 100 executes an analysis mode 120 for synthesizing results during the measurement period of the hysteresis measurement mode 110. The analysis mode 120 can be broadly divided into an analysis result by time, which is an analysis result according to a user's use time of the smart scale 10 and an analysis result by location, which is an analysis result according to a place where the user's smart scale 10 is used.

In the hourly analysis, results such as daily analysis divided into morning, afternoon, and evening time zones, analysis by day of the week divided from Monday to Sunday, analysis by holiday divided between weekdays and weekends, other weekly analysis, and monthly analysis can be derived. have. In addition, the analysis for each space may be performed by dividing the smart scale 10 into locations of use, for example, a gym, a workplace, or a home, and the result of which the body composition state is maintained excellently can be derived. Depending on the result of the analysis mode 120, the user's body composition increase/decrease pattern analysis may be performed in various ways.

When the user's body composition increase/decrease pattern is recognized through the analysis mode 120, the server 100 may execute a similar history search mode 130 that is comparable to the user's body composition pattern based on the analysis result. . When the similar history search mode 130 is executed in the server 100, the success or failure examples of others similar to the current user's history are matched, and accordingly, the user can be alerted to health management. That is, according to the implementation of the similar history search mode 130, the server 100 may provide the user with the amount of exercise, exercise method, diet diet, etc. of the other person while proposing a success case of another person similar to the current user's history. Alternatively, if the current user's history is close to the failure case, the risk index for this may be calculated, thereby allowing the user to realize the necessity for physical management.

As described above, the user's history, that is, the similarity history to be compared with the self-history may be searched based on the degree of correspondence between the self-history and the similarity history and the weights of factors that determine the degree of correspondence.

The factor that determines the degree of correspondence between histories can be composed of various conditions. For example, as ages between personal and similar histories are similar, a higher degree of agreement may be obtained, and as the measurement period is longer and the number of measurements is increased, the degree of agreement between the histories may increase. In other words, in the history change pattern of oneself and others, the accuracy of the change pattern compared and analyzed for one week will be higher than the change pattern that was compared and analyzed for only one day, and the accuracy is higher when the corresponding history is distributed in the same month. It will mean being elevated.

In addition, as the frequency and time of use of the smart scale 10 of oneself and others are similar, the accuracy of the match between both histories will be higher. And, the accuracy of the similarity of body fat will be higher than the similarity of weight between the two histories, and the accuracy of the similarity of obesity will be higher than the similarity of body fat. In addition, if you and others have similar living areas, work in similar industries, and have similar meal times, the accuracy of the match between the two histories will increase.

A number of factors that determine the degree of correspondence between these histories may be weighted according to their importance. For example, an information factor about age may be given the greatest weight because its importance is greater than that of other factors. In addition, since the information factor for the measurement period and number of times has a higher importance than other factors other than the information factor for age, the second largest weight is given, and weights are sequentially weighted according to the frequency of use, obesity, and living environment. Can be given.

In this way, in the similarity history search mode 130 of the server 100, an appropriate similarity history may be searched according to the result calculated based on the degree of correspondence between the personal history and the other person's history and the weights of factors that determine the corresponding degree of match. have. Only one of the similar histories may be searched, or success cases and failure cases may be searched respectively as necessary.

When the similarity history to be compared is derived according to the implementation of the similarity history search mode 130, the server 100 reviews whether the current self-history pattern is close to one of a success case or a failure case. A recommendation mode 140 suggesting an amount of exercise, diet, and the like is performed.

First, when the recommendation mode 140 is executed, the server 100 reviews the user's history pattern and compares it with a success case. Calculate the probability of success. Then, the server 100 proposes a specific future health management schedule to the user based on the corresponding success probability. For example, the server 100 recommends information on the amount of exercise, exercise method, diet diet, etc. of another person based on a success case to the user, and in particular, the diet diet may be linked to orders and payments when necessary.

Processes of the similar history search mode 130 and the recommendation mode 140 are shown in more detail in FIGS. 4 and 5.

Referring to the drawings, the server 100 performs a detailed analysis of the hysteresis through the hysteresis measurement mode 110 and the analysis mode 120 (S10). Then, the server 100 compares and analyzes other's histories and his/her histories, and analyzes the degree of correspondence between the corresponding histories. In addition, a weight is assigned to factors that determine the degree of agreement between the two histories, and the similar histories to be compared with the self-history are searched (S20).

In order to determine whether the similar history derived through such a process is indeed consistent with the self-history, a review is performed in preparation for the self-history and the similar history for a certain period (S30). After going through the review process, the server 100 determines whether the comparison result between the histories falls within an error range (S40). If it is outside the error range, after resetting the degree of agreement between the two histories and the weight between the factors that determine the degree of agreement, the process returns to step S20 and re-searches the similarity histories.

If it is determined that the server 100 has searched for an appropriate similar history to be compared with the personal history, the user’s target achievement success rate is calculated by comparing the current history pattern with the similar history (S50). In addition, the server 100 activates the recommendation mode 140 to present a future health care schedule for increasing the success probability (S60).

For example, the server 100 may perform a similar history recommendation mode 141 corresponding to a success case. The similar history recommendation mode 141 may be a recommendation regarding the exercise method 142 of another person, or may be a recommendation regarding a diet diet 143. In addition, the server 100 may implement an appropriate lifestyle recommendation mode 145 based on the user's living environment. For example, in the case of an office worker or a salesperson who travels frequently, the lifestyle recommendation mode 145 includes an activity 146 for each region that suggests a user's exercise program or a specific menu of a restaurant for each region that suggests a user's diet program ( 147).

The recommendation for the diet diet 143 may be made based on the user's current health status by synthesizing the user's body composition analysis result and the user's heart rate analysis result through a heart rate monitor. Specifically, when information on the current user's health status is transmitted to the server 100 through the smart weight scale 10 and the heart rate monitor, the server 100 analyzes the data and recommends the most effective diet lunch menu to the user. do. For example, if the body composition result is normal but the heart rate is irregular, a diet lunch menu rich in fiber necessary for heart rate management may be recommended to the user.

When such health management schedule recommendation is completed, the server 100 may link payment information in cooperation with a company affiliated in advance so that the user can immediately search for and pay for the diet diet 143 and the like (S70). As described above, as the server 100 recommends a meal to the user and links payment information for purchasing a corresponding meal, the user's convenience may be greatly improved.

When the use of the smart scale 10 is completed during the period set by the user according to the above process, the server 100 evaluates the user's history during the period, and if the user initially sets a health management goal. According to whether the target is reached, the reward mode 150 is activated to provide appropriate rewards to the user.

The compensation mode 150 is a mode that is exercised when a user inputs an appropriate goal at the beginning of use of the smart scale 10, and is a mode in which the level of compensation is determined according to the level of achievement of the user's goal. This compensation mode 150 may increase user participation by providing motivation for health management to the user.

The progress of the compensation mode 150 is shown in detail in FIG. 6.

Referring to the drawings, first, when a user generates a self-history using the smart scale 10 for a certain period of time, the server 100 searches for a similar history that can be compared with the self-history. In addition, the server 100 calculates a health management target value of the user through a comparison review between the self-history and the similar history (S100).

When the health management target value is calculated, a period for the user to reach the target value is set (S200). The period of reaching the target value may be arbitrarily selected by the user, but the server 100 may recommend a period in which the user's health is not unreasonable.

When this process is completed, the server 100 determines whether or not the target provided to the user has been properly calculated (S300). To determine whether or not to calculate an appropriate goal, factors such as analysis of the user's body composition, heart rate analysis, environment analysis, similar history analysis, and goal achievement period should be reviewed from various angles. If it is determined that the target value given to the user is not appropriate, the server 100 completely reviews the similarity history and the set period of reaching the target value (S310), returns to step S100, and calculates a new target value again based on the reviewed content. do.

On the contrary, if it is determined that the user has been given an appropriate target value, the user inputs the timing and method of measuring his/her history through the smart scale 10 (S400), and the server 100 proceeds to the target during the target achievement period. It is constantly reviewed as to whether it is being performed (S500).

When the measurement period ends through such a process, the server 100 derives and analyzes the measured result value through the smart scale 10 and notifies the user of the result (S600). When the user checks the result, the server 100 determines the degree of compensation according to the result value (S700). For example, if the calculated result achieves 50% of the original target value, only 50% of the initial compensation plan is paid to the user. These rewards can be provided to users in various forms. For example, the user may be provided with a meal ticket for a diet diet linked in the recommendation mode 140, as another example, an activity use right, and another example, a gym use right, and the like.

When the awarding of such rewards is completed, all the corresponding data are converted into data and stored in the server 100 (S800). The stored data may be used as a similar history of others in the future.

As described above, according to the present invention, there is an advantage in that the user's health management can be more efficiently performed, and the user's participation and satisfaction can be greatly improved as appropriate motivation is provided to the user who uses the system.

The foregoing description of the present application is for illustrative purposes only, and those of ordinary skill in the art to which the present application pertains will be able to understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present application. Therefore, it should be understood that the embodiments described above are illustrative and non-limiting in all respects. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as being distributed may also be implemented in a combined form.

The scope of the present application is indicated by the claims to be described later rather than the detailed description, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present application.

[Explanation of code]

10: smart scale 20: stepping plate

30: handle 40: support

50: monitor 100: server

110: hysteresis measurement mode 120: analysis mode

130: similar history search mode 140: recommended mode

150: compensation mode 200: smartphone

The present invention can be applied and utilized in a variety of fields similar to or related to the field of healthcare and health management, smart scale, personalized health scheduling service providing field, individual diet management field, rehabilitation medical field, and related products and The reliability and competitiveness of the system can be improved.

Claims

A smart scale 10 capable of recognizing a user's bio-signal and measuring body fat for each body part of the user;

An electronic device (200) interlocked with the smart scale (10) and allowing a user to check a result value measured from the smart scale (10); And

Including a server 100 that exchanges data with the smart scale 10 and the electronic device 200 and stores a record of the user's health management,

The server 100, a health care system using a smart scale, characterized in that it includes a recommendation mode 140 for analyzing the current health state of the user and suggesting a health management program to the user.
The method of claim 1,

The smart scale 10,

A handle 30 that can be gripped by a user;

A stepping plate 20 that provides a footrest to recognize a user's biometric signal; And

Includes a support 40 connecting the handle 30 and the stepping plate 20 to each other,

Each of the handle 30 and the stepping plate 20 is provided with sensing units 25 and 35 to which electrical stimulation is applied to measure the user's body fat in a bioelectrode impedance method. Healthcare system.
The method of claim 2,

The smart scale 10,

A smart scale, characterized in that it is an 8-point touch-type electrode type scale, in which four sensing units 25 are formed on the handle 30 and four sensing units 35 are formed on the stepping plate 20. Used healthcare system.
The method of claim 1,

When the smart scale 10 is initially used, the smart scale 10 and the electronic device 200 are interlocked with each other through a Bluetooth method,

The server 300 converts and stores information on the user's bio-signals recognized by the smart scale 10 and the user's information input to the electronic device 200 into basic data. Health care system using a scale.
The method of claim 4,

After the initial use registration of the smart scale 10 is completed, when the smart scale 10 is connected to the Internet network, new data newly measured by the smart scale 10 is transmitted to the server 300,

The server (300) is a healthcare system using a smart scale, characterized in that the conversion of the pre-stored basic data and the new data together with the electronic device (200).
The method of claim 1,

The server 100,

A hysteresis measurement mode 110 for tracking and managing changes in the user's body when the user uses the smart scale 10 during a predetermined measurement period; And

Health care system using a smart scale, characterized in that it further comprises an analysis mode (120) for checking a user's body change pattern based on the result value calculated in the hysteresis measurement mode (110).
The method of claim 6,

The hysteresis measurement mode 110 is divided into a periodic measurement that measures a user's body change at regular intervals and an irregular measurement that randomly measures a user's body change within the predetermined measurement period,

The analysis mode 120 is a health care using a smart scale, characterized in that it is divided into a time-based analysis that divides and analyzes the user's body change pattern by period, and a space-by-space analysis that divides and analyzes the body change pattern by place. system.
The method of claim 6,

The server 100,

A similarity history search mode that derives a similarity history to be compared with the history based on a degree of agreement with the hysteresis calculated in the hysteresis measurement mode 110 and a weight for a factor that determines the degree of matching A healthcare system using a smart scale, characterized in that it further comprises 130).
The method of claim 8,

The factor considered in the similarity history search mode 130 is,

Information on the user's age, information on the measurement period of the smart scale 10, information on the frequency of use of the smart scale 10, information on the measurement method for the user's body change, and the user's living environment Health care system using a smart scale, characterized in that it includes at least one of the information.
The method of claim 8,

The recommendation mode 140 compares the similar history derived through the similarity history search mode 130 and the current user's personal history measured through the self-history measurement mode 110, and provides a success case of others to the user. And a healthcare system using a smart scale, characterized in that presenting a lifestyle.
The method of claim 10,

The success case of the other person includes information on the diet diet 143 of another person corresponding to the similar history,

The recommendation mode 140 is a healthcare system using a smart scale, characterized in that linked with payment information for selling the diet diet (143).
The method of claim 1,

The server 100,

After comparing the information on the current self-history and the information on the similar history derived through the similar history search mode 130 to calculate a target value, the user is informed according to whether the target value is reached for a certain period and the degree of arrival Health care system using a smart scale, characterized in that it further comprises a compensation mode 150 for granting a certain compensation.