WO2012008671A1

WO2012008671A1 - System for selecting mattress model

Info

Publication number: WO2012008671A1
Application number: PCT/KR2011/000674
Authority: WO
Inventors: Jung Yong Kim; Jung Ho Ahn; Young Sung Shin; Seung Nam Min; Min Ho Lee
Original assignee: Simmons-K.Co.,Ltd
Priority date: 2010-07-13
Filing date: 2011-01-31
Publication date: 2012-01-19
Also published as: KR20120006766A; KR101197215B1

Abstract

The present invention relates to a system for selecting a mattress model for selecting and recommending an optimum mattress according to body characteristics. The system for selecting a mattress model includes at least one measuring unit for measuring a body characteristic data of a user, a control terminal for substituting the body characteristic data received from the measuring unit for a variable in a preset linear recursion relation as a user characteristic data, and selecting at least one mattress model based on a result of regression analysis of the linear recursion relation, and a display unit for displaying information on the result of the regression analysis and the mattress model selected thus which are produced from the control terminal.

Description

SYSTEM FOR SELECTING MATTRESS MODEL

The present invention relates to a system for selecting a mattress model to select and recommend an optimum mattress according to body characteristics.

Currently, most persons sleep at beds. If the bed is not comfortable during the sleep, the person fails to take a sound sleep, adding fatigue to a body of the person. The mattress related to the fatigue of the body of the person the most closely thus is the most important part of the bed.

In general, the person can take the best sleep if a body pressure distribution is uniform when the person lays down himself (or herself) on the mattress. However, if the body pressure distribution is not uniform, causing heavy bending of a waist or distortion of a posture of other particular portion of the body, the fatigue of the body is accelerated. Particularly, if the mattress is too hard, or too soft, failing to maintain a natural curve of the waist, no sound sleep can be secured.

Though mattresses having various characteristics are coming to market ceaselessly, since most of the mattresses are fabricated according to generalized standards, individual goodness of fit has not been taken into account.

However, since unit cost of the fabrication of the mattress becomes high if the mattress is fabricated only taking the individual goodness of fit into account, it is also required to take an appropriate fabrication cost into account. Accordingly, a scheme is required, in which an optimum mattress is selected for an individual taking both personal goodness of fit and the mattress fabrication cost into account.

As factors for taking the individual goodness of fit to the mattress into account, different variables, such as individual body characteristics, habit, age, and so on, can be defined. However, a scheme for applying the different variables to different individuals, and a reference relational expression for obtaining an objective result by applying the different variables to different individuals, are required.

However, the most important thing is what form of a reference relational expression will be used. And, after the reference relational expression is formulated, a process is important, in which, the optimum mattress is selected with reference to a result of substitution of the individual different variables for variables in the reference relational expression.

To solve the problems, an object of the present invention is to provide a system for selecting an optimum mattress model with reference to an algorithm which uses regression analysis.

Another object of the present invention is to provide a system for selecting the best fit optimum mattress model by using a logical configuration which applies individually definable different variables, such as body characteristics, habit, age, and so on, to multiple recursion relation based on regression analysis.

To achieve these objects and other advantages and in accordance with the purpose of the invention, as embodied and broadly described herein, a system for selecting a mattress model includes at least one measuring unit for measuring a body characteristic data of a user, a control terminal for substituting the body characteristic data received from the measuring unit for a variable in a preset linear recursion relation as a user characteristic data, and selecting at least one mattress model based on a result of regression analysis of the linear recursion relation, and a display unit for displaying information on the result of the regression analysis and the mattress model selected thus which are produced from the control terminal.

Preferably, the control terminal has an application for controlling operation and measurement of the measuring unit, displaying of the display unit, and selecting the at least one mattress model from the result of the regression analysis produced by substituting the user characteristic data for variables in the linear recursion relation.

In this instance, the application displays enquete on the display unit for selection of a user's sex, input of personal information, and selection of personal habit, and producing the result of the regression analysis by substituting the personal characteristic data which is a result of the enquete for the variables in the linear recursion relation further as the user characteristic data.

And, the application displays guidance to a measuring procedure of the measuring unit on the display unit, a sampling graph for determining validity of the body characteristic data received from the measuring unit, a result of the measurement received from the measuring unit in real time, and the mattress model selected thus and information on the mattress model selected thus. In this instance, the information on the mattress model selected thus includes a model number, an image, price and features of the mattress model selected thus.

Preferably, the measuring unit can include a body pressure distribution measuring instrument for measuring a body pressure concentration of each part of the body applied to the mattress for measuring a body pressure distribution which corresponds to one of the body characteristic data, and a cardiac rate measuring instrument for measuring a cardiac rate which corresponds to one of the body characteristic data.

Preferably, the control terminal sets the linear recursion relation, the control terminal configured to: dertermining the independent variables and the dependent variable with reference to the user characteristic data of a plurality of users who belong to an experimental group for making the regression analysis, defining the linear recursion relation for correlation analysis between the independent variables and the dependent variable, producing coefficient values of the independent variables which corresponds to regression coefficient of the linear recursion relation by using the user characteristic data of a plurality of users who belong to the experimental group, and setting the linear recursion relation having the coefficient values of the independent variables produced thus applied thereto

In this instance, the linear recursion relation is a multiple recursion relation defined as Dependent variable y = a coefficient value of a first independent variable * X₁ + a coefficient value of a second independent variable * X₂ + a coefficient value of a third independent variable * X₃, a coefficient value of the independent variable includes coefficient values of the first to third independent variables, and the independent variable includes X₁, X₂, and X₃ which represent categories different from one another with reference to the user characteristic data of the users. In this instance, the user characteristic data includes the body characteristic data having a body pressure distribution and a cardiac rate and the personal characteristic data which corresponds to a enquete result of the user, wherein the body characteristic data and the personal characteristic data are set as an independent variable category which corresponds to X₁, X₂, and X₃, and the regression analysis result for selecting at least one mattress model is set as the dependent variable y.

Preferably, the control terminal produces the result of the regression analysis as a value of a dependent variable of the linear recursion relation by substituting the body characteristic data and the personal characteristic data for the variables in the linear recursion relation as independent variables thereof, and selects at least one mattress model which corresponds to the result of the regression analysis produced thus. In this instance, the control terminal selects a first to Nth mattress models classified with reference to strength of the mattress in advance, and selects at least one mattress model which corresponds to the result of the regression analysis produced thus.

Preferably, the control terminal sets linear recursion relations different with user age groups, and the user characteristic data is substituted for the independent variables in the linear recursion relation of a relevant user age groups.

Preferably, the control terminal further includes a data base for storing information on the result of the regression analysis and the mattress model selected thus. Particularly, the control terminal assigns a unique identification number to the user, and transmits information stored in the data base to a registered user's terminal through a network after authentication of the user identification code.

The present invention has following advantageous effects.

Since the system for selecting a mattress model of the present invention selects one or more than one mattress model for the user by using algorithm applied to a multiple recursion relation with reference to different variables, such as body characteristics, habit, age, and so on, a mattress can be selected taking individual goodness of fit into account the best.

And, since the system helps the user to select the best fit bed mattress, the mattress will not cause any body trouble and help the user to take sound sleep.

The accompanying drawings, which are included to provide further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiments of the disclosure and together with the description serve to explain the principle of the disclosure.

In the drawings:

FIG. 1 illustrates a table showing an example in which strength differences of first to Nth mattress models of the present invention are measured and cluster analysis on the mattress models according to the strength is preformed.

FIG. 2 illustrates a block diagram showing an entire configuration of a mattress model selection system in accordance with a preferred embodiment of the present invention.

FIG. 3 illustrates a flow chart showing the steps of a method for selecting a mattress model by using regression analysis at a control terminal in a system in accordance with a preferred embodiment of the present invention.

Reference will now be made in detail to the specific embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Configuration and operation of the present invention shown on drawings attached hereto and described with reference to the drawings is described as at least one of embodiments of the present invention. However, technical aspects and essential configuration and operation of the present invention are not limited by above description.

A system for selecting a mattress model in accordance with a preferred embodiment of the present invention will be described in detail, with reference to attached drawings.

Referring to FIG. 2, the system includes a plurality of

measuring units

30, 31, and 32, a control terminal 20 and a display unit 10. The control terminal has an application for performing a process for selecting a mattress model described with reference to FIG. 3, and a data base 21 for storing different data. The application, a logic system of the control terminal, can be understood as a function of the control terminal 20.

The

measuring units

30, 31, and 32 having first to

third measuring units

30, 31, and 32 are configurations for measuring user's body characteristic data. In this instance, the user is an objective person for recommending the mattress model.

The first measuring unit 30 measures a body pressure distribution which is a pressure concentration on a mattress, and can be, for an example, a body pressure distribution measuring instrument which measures the body pressure concentration of each part of the body applied to the mattress.

The second measuring unit 31 can be, for an example, a cardiac rate measuring instrument for measuring a cardiac rate to detect an extent of relaxation of the body.

The third measuring unit 32 can be, for an example, an oxygen saturation measuring instrument for measuring a degree of saturation of oxygen for detecting an extent of relaxation of the body.

In the meantime, the body characteristics measured at the first and

second measuring units

30 and 31, i.e., the body pressure distribution and the cardiac rate, are used for selection of the mattress.

The control terminal, being a logical configuration, has an application of an algorithm with regression analysis applied thereto, and selects at least one mattress model by using the body characteristic data received from the measuring units 30 ~ 32 as user characteristic data. Particularly, the control terminal 20 uses, not only the body characteristic data, but also an individual characteristic data obtained as a result of enquete to the user as the user characteristic data additionally in selection of the mattress model.

The control terminal 20 substitutes the body characteristic data and the personal characteristic data for the variables of a preset linear recursion relation, to obtain a regression analysis result (i.e., a value of dependent variable) of the linear recursion relation, and selects at least one mattress model from the result. The control terminal 20 provides information on a model number, an image, price, and characteristics of a mattress model as detailed information on the mattress selected thus. According to this, the display unit 10 displays the detailed information on the mattress model provided from the control terminal 20.

In the meantime, the control terminal 20 has the data base 21 having the detailed information on a various mattress models stored therein. And, the data base 21 has the body characteristic data measured by the measuring units 30 ~ 32 stored therein sorted by users, and the personal characteristic data obtained as the result of enquete to the users stored therein sorted by users.

Particularly, referring to FIG. 1, the detailed information on the mattress model is stored as a cluster analysis table, which cluster analysis is made according to strength of the mattress models.

The display unit 10 displays information on the mattress model and a process for making enquete to the user. That is, the display unit 10 is a kind of user interface for making enquete to the user.

FIG. 1 illustrates a table showing an example in which strength differences of first to Nth mattress models of the present invention are measured and cluster analysis on the mattress models is preformed according to the strength.

Referring to FIG. 1, the cluster analysis table is stored in the data base 21, which cluster analysis is made according to strength of the mattress models with reference to the result of measurement of the strength differences of first to Nth mattress models.

Referring to FIG. 1, the first mattress model corresponds to a first group, the second and sixth mattress models correspond to a second group, the third mattress model corresponds to a third group, the fourth and fifth mattress models correspond to a fourth group, and an Nth mattress model corresponds to fifth group. At the end, the groups are sorted with reference to mattress strength which is an extent of depression of the mattress (i.e., a depth of depression by a specific reference pressure).

The data at the table 1 is a result of regression analysis produced finally, i.e., one for comparing to the dependent variable y values produced by the application in the control terminal 20. The control terminal 20 selects at least one group corresponding to the dependent variable y value produced thus, and forwards a result selected thus as a result of selection of the mattress model.

In the meantime, the dependent variable y value is on the extent of muscle relaxation. In the present invention, the extent of muscle relaxation is set as the dependent variable by using a principle in which the extent of muscle relaxation is related to the mattress strength, and the mattress model is selected by a method in which the dependent variable y is estimated by using the body pressure distribution and the cardiac rate which have good correlation to the muscle relaxation that is the dependent variable as independent variables of the linear multiple recursion relation.

The application at the control terminal 20 has the first to Nth mattress models applied thereto, and at least one mattress model which corresponds to a resultant value of the regression analysis of the process for selecting the mattress model to be described later is selected from the first to Nth mattress models.

The application uses the regression analysis in the process for selecting the mattress model.

The regression analysis is used for estimating the other variable from one variable in a case two variables are given, or investigating a relation between the two variables.

Particularly, the application of the present invention uses the multiple regression analysis in which the linear multiple recursion relation which is a mathematical model on correlation between the independent variables and the dependent variable is set in advance, and the body characteristic data and the personal characteristic data substitute for the independent variables in the linear multiple recursion relation, for estimating the dependent variable in the linear multiple recursion relation.

As another example, the control terminal 20 of the present invention can set linear multiple recursion relations different from each other, or can also produce a regression analysis result by substituting the user characteristic data of the user (the body characteristic data and the personal characteristic data) for the independent variables in the linear recursion relation.

The application at the control terminal 20 will be described in detail, with reference to FIG. 3.

FIG. 3 illustrates a flow chart showing the steps of a method for selecting a mattress model by using regression analysis at the control terminal in a system in accordance with a preferred embodiment of the present invention.

The application at the control terminal 20 controls operation of the plurality of measuring units 30 ~ 32 and measurement of the measuring units 30 ~ 32. And, the application controls display on the display unit 10. Particularly, the application selects at least one mattress model from a regression analysis result produced by substituting the user characteristic data for variables in a preset linear recursion relation.

If the application at the control terminal 20 is put into operation, the display unit 10 displays an operation screen. Thereafter, a series of steps is displayed on the display unit 10 until the mattress model is selected.

The application measures the body characteristic data and the personal characteristic data to be substituted for variables in the linear multiple recursion relation, later (S10).

The application selects a sex of the user, and a mattress type (for an example, for one person, or two person) at first, inputs personal information, such as name, a place to call, and an address, displays a page on the display unit 10 for making enquete personal habit, such as a preferred mattress (for an example, one of a hard mattress and a soft mattress), and experience of use of the mattress, and stores answers on the enquete at the data base 21 as a result of the enquete.

And, the application displays guidance to a measuring procedure of the measuring units 30 ~ 32 on the display unit 10, and a sampling graph for determining validity of the body characteristic data received from the measuring units 30 ~ 32 before the measurement is started. And, the application displays a measured result received from the measuring unit 30 ~ 32 in a real time after starting of the measurement.

After finishing the measurement of the personal characteristic data and the body characteristic data thus, the application stores a result of the measurement at the data base 21.

And, the application substitutes a result of the measurement, i.e., the personal characteristic data which is a result of the enquete, and the body characteristic data measured thus for variables in the linear multiple recursion relation as the user characteristic data (S20).

The measured result is substituted for independent variables in a preset equation 1 which is the linear multiple recursion relation.

Dependent variable y = a coefficient value of a first independent variable * X₁ + a coefficient value of a second independent variable * X₂ + a coefficient value of a third independent variable * X₃ + B -------------------------- (1)

The independent variables in the equation 1 include X₁, X₂, and X₃ which denote categories different from one another with reference to the user characteristic data of the user. In the present invention, the body characteristic data and the personal characteristic data are set as categories of the independent variables X₁, X₂ and X₃, and a result of regression analysis for selecting at least one mattress model is set as the dependent variable y.

The linear multiple recursion relation set at the control terminal 20 is set as follows.

The independent variables and the dependent variables are determined from the user characteristic data on a plurality of users who belong to an experimental group, the linear recursion relation for making correlation analysis between the independent variables and the dependent variables is defined as the equation 1, coefficient values of the independent variables which correspond to regression coefficients of the linear recursion relation are calculated by using the user characteristic data of the plurality of users who belong to the experimental group, and the linear recursion relation having the coefficient values of the independent variables calculated thus is set.

In detail, correlations of the user characteristic data of the plurality of user who belong to the experimental group are analyzed, to determine the independent variables and the dependent variables for making the regression analysis at first. In the present invention, the extent of the muscle relaxation y is determined as the dependent variable, and the body pressure distribution X₁, the cardiac rate X₂ and the personal characteristic data X₃ are determined as the independent variables. Of course, the degree of saturation of oxygen X₄ may further determined as the independent variable. Then, the linear multiple recursion relation is defined for correlation analysis between the independent variables and the dependent variables determined thus.

In the equation 1, the coefficient values of the independent variables include coefficient values of the first to third independent variables which are produced from the user characteristic data of the plurality of users who belongs to the experimental group.

X₁, X₂, and X₃ in the equation 1 are values to be substituted for producing the dependent variable y, i.e., objects to be substituted for the body characteristic data and the personal characteristic data which are results of the measurements.

As described before, according to the correlation analysis, X₁ is an independent variable for representing the body pressure, X₂ is an independent variable for representing the cardiac rate, and X₃ is an independent variable for representing the personal characteristic obtained as the result of enquete.

Accordingly, the coefficient value of the first independent variable is a coefficient value for representing correlation between the extent of muscle relaxation y and the body pressure distribution, the coefficient value of the second independent variable is a coefficient value for representing correlation between the extent of muscle relaxation y and the cardiac rate, and the coefficient value of the third independent variable is a coefficient value for representing correlation between the extent of muscle relaxation y and the personal characteristic.

In the meantime, as described before, the coefficient value of the fourth independent variable representing correlation between the extent of muscle relaxation y and the independent variable X₄ on the degree of oxygen saturation can also be applied to the linear multiple recursion relation of the equation 1, additionally.

The present invention utilizes that the independent variables having high correlation with the dependent variable have positive relationships. In this instance, since the degree of oxygen saturation has low correlation with the extent of muscle relaxation which corresponds to a category of the dependent variable, the degree of oxygen saturation can be excluded from the independent variable.

And, a constant B can be applied to the equation 1 additionally, for estimating the dependent variable from the linear multiple recursion relation. That is, the linear multiple recursion relation can consist of a constant B together with other independent variables.

In the meantime, in the equation 1, the coefficient values of the first and third independent variables and the constant B have positive values, and the coefficient value of the second independent variable has a negative value.

The coefficient values of the independent variables are produced by measuring the body pressure distribution, the cardiac rate, the degree of oxygen saturation, and the extent of muscle relaxation as the body characteristic data of the plurality of users who belong to the experimental group, and measuring the personal characteristic data with reference to the result of enquete including personal information and habit (for an example, a sleeping time, or posture) of the plurality of users who belong to the experimental group.

Optionally, in the present invention, the experimental group is sorted into age groups, and an age group linear multiple recursion relation is set by using the body characteristic data and the personal characteristic data measured in the age groups. In this instance, the age group linear multiple recursion relation has the coefficient values of the independent variables different with the age groups since the body characteristic data and the personal characteristic data for one age group will be different from that of another age group.

The application produces the value of the dependent variable y which is a result of the regression analysis by substituting the body characteristic data measured with the measuring units 30 ~ 32 together with the personal characteristic data which is the result of the enquete for the variables in the linear multiple recursion relation of the equation 1 as the user characteristic data (S30).

The application selects at least one mattress model corresponding to the result of the regression analysis produced thus (S40). That is, the result of the regression analysis produced thus is a value representing the extent of muscle relaxation which is the dependent variable. In the present invention, groups sorted as shown in FIG. 1 are set in advance according to the extents of muscle relaxation, and at least one mattress model which corresponds to the result of the regression analysis is selected from the first to Nth mattress models shown in FIG. 1 through a process in which the result of the regression analysis produced actually is compared to the groups to find to which group the result falls on.

Accordingly, the application retrieves detailed information on the mattress model selected thus (information on a model number, an image, price, and features of the mattress) from the data base 21 and displays the same on the display unit 10 (S50).

In the meantime, the control terminal 20 assigns a unique identification code to the user, stores the data of the user relating to the identification code (the body characteristic data, the personal characteristic data, the result of the regression analysis, and the mattress model selected thus).

And, if the user requests access to the data, the information stored in the data base 21 can be transmitted to a user's terminal registered in advance through a network after authentication of the user identification code.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.

Claims

A system for selecting a mattress model comprising:

at least one measuring unit for measuring a body characteristic data of a user;

a control terminal for substituting the body characteristic data received from the measuring unit for a variable in a preset linear recursion relation as a user characteristic data, and selecting at least one mattress model based on a result of regression analysis of the linear recursion relation; and

a display unit for displaying information on the result of the regression analysis and the mattress model selected thus which are produced from the control terminal.
The system as claimed in claim 1, wherein the control terminal has an application for controlling operation and measurement of the measuring unit, displaying of the display unit, and selecting the at least one mattress model from the result of the regression analysis produced by substituting the user characteristic data for variables in the linear recursion relation.
The system as claimed in claim 1, wherein the application displays enquete on the display unit for selection of a user's sex, input of personal information, and selection of personal habit, and producing the result of the regression analysis by substituting the personal characteristic data which is a result of the enquete for the variables in the linear recursion relation further as the user characteristic data.
The system as claimed in claim 3, wherein the control terminal produces the result of the regression analysis as a value of a dependent variable of the linear recursion relation by substituting the body characteristic data and the personal characteristic data for the variables in the linear recursion relation as independent variables thereof, and selects at least one mattress model which corresponds to the result of the regression analysis produced thus.
The system as claimed in claim 4, wherein the control terminal presets a first to Nth mattress models classified with reference to strength of the mattress, and selects at least one mattress model which corresponds to the result of the regression analysis produced thus.
The system as claimed in claim 2, wherein the application displays guidance to a measuring procedure of the measuring unit on the display unit, a sampling graph for determining validity of the body characteristic data received from the measuring unit, a result of the measurement received from the measuring unit in real time, and the mattress model selected thus and information on the mattress model selected thus.
The system as claimed in claim 6, wherein the information on the mattress model selected thus includes a model number, an image, price and features of the mattress model selected thus.
The system as claimed in claim 1, wherein the measuring unit includes;

a body pressure distribution measuring instrument for measuring a body pressure concentration of each part of the body applied to the mattress for measuring a body pressure distribution which corresponds to one of the body characteristic data, and

a cardiac rate measuring instrument for measuring a cardiac rate which corresponds to one of the body characteristic data.
The system as claimed in claim 1, wherein the control terminal sets the linear recursion relation, the control terminal configured to:

dertermining the independent variables and the dependent variable with reference to the user characteristic data of a plurality of users who belong to an experimental group for making the regression analysis,

defining the linear recursion relation for correlation analysis between the independent variables and the dependent variable,

producing coefficient values of the independent variables which corresponds to regression coefficient of the linear recursion relation by using the user characteristic data of a plurality of users who belong to the experimental group, and

setting the linear recursion relation having the coefficient values of the independent variables produced thus applied thereto.
The system as claimed in claim 9, wherein the linear recursion relation is a multiple recursion relation defined as Dependent variable y = a coefficient value of a first independent variable * X₁ + a coefficient value of a second independent variable * X₂ + a coefficient value of a third independent variable * X₃,

a coefficient value of the independent variable includes coefficient values of the first to third independent variables, and

the independent variable includes X₁, X₂, and X₃ which represent categories different from one another with reference to the user characteristic data of the users.
The system as claimed in claim 10, wherein the user characteristic data includes the body characteristic data having a body pressure distribution and a cardiac rate and the personal characteristic data which corresponds to an enquete result of the user,

wherein the body characteristic data and the personal characteristic data are set as an independent variable category which corresponds to X₁, X₂, and X₃, and the regression analysis result for selecting at least one mattress model is set as the dependent variable y.
The system as claimed in claim 1, wherein the control terminal sets linear recursion relations different with user age groups, and

the user characteristic data is substituted for the independent variables in the linear recursion relation of a relevant user age group.
The system as claimed in claim 1, wherein the control terminal further includes a data base for storing information on the result of the regression analysis and the mattress model selected thus.
The system as claimed in claim 13, wherein the control terminal assigns a unique identification number to the user, and transmits information stored in the data base to a registered user's terminal through a network after authentication of the user identification code.