Clothing size acquisition system, clothing size acquisition program, clothing selection assistance method, and computer-readable non-transitory storage medium

Abstract

A plurality of body composition data corresponding to clothing sizes representing sizes of clothes worn by customers and body composition data of customers measured by a measuring device are established, a clothing size of a customer is estimated, a degree of fitness of the estimated clothing size to the customer is calculated, a salesclerk confirms the estimated clothing size and the degree of fitness displayed on a terminal device, and selection assistance of clothes for the customer is performed.

Description

[0001] Cross-reference of related applications

[0002] This application claims priority to Japanese Patent Application No. 2019-94551, filed on May 20, 2019, the contents of which are incorporated herein by reference. Technical Field

[0003] This invention relates to a clothing size acquisition system, a clothing size acquisition program, and a clothing selection assistance method. Background Technology

[0004] The size of clothing and other garments is determined based on information such as height, waist circumference, and shoulder width. Therefore, when buying clothes in a store, the salesperson measures the buyer's waist circumference, shoulder width, etc., but this is a cumbersome task for them. Furthermore, it is difficult for the buyer to measure their own waist circumference and shoulder width without assistance. On the other hand, values ​​related to the entire body, such as height and weight, are easier to measure. However, clothing, such as jackets and trousers, is generally worn on the upper or lower body, so accurate determination of clothing size cannot be achieved using measurements related to the entire body.

[0005] Therefore, as disclosed in Japanese Patent Application Publication No. 2016-123589, a device has been developed that acquires body shape data representing the three-dimensional shape of the body and obtains body information of the subject.

[0006] The body information acquisition device disclosed in Japanese Patent Application Publication No. 2016-123589 generates a parallel projection image formed by parallel projection of the three-dimensional shape of the body of an object represented by body shape data. For the body shape data, one or more specific Y positions for which body information should be acquired are set, and the length of the parallel projection image at the specific Y position in a direction orthogonal to the Y axis is acquired as one of the body information of the object. Summary of the Invention

[0007] However, methods for measuring the three-dimensional shape of the body, such as those disclosed in Japanese Patent Application Publication No. 2016-123589, involve numerous measurement sites, requiring significant time and complexity in measurement and processing. Furthermore, accurate acquisition of body shape information is impossible when the subject is clothed. Additionally, measuring the three-dimensional shape of the body necessitates investment in new equipment, such as 3D scanners capable of scanning people.

[0008] Therefore, the object of the present invention is to provide a clothing size acquisition system, clothing size acquisition program, clothing selection assistance method, and computer-readable non-transitory storage medium that can easily obtain clothing size that is more suitable for the wearer of the clothing.

[0009] Solution for solving the problem

[0010] A clothing size acquisition system includes: a biometric acquisition unit for acquiring biometric information of a presumed subject; a storage unit for storing multiple biometric information corresponding to clothing sizes representing the size of clothing worn by the presumed subject; and a clothing size estimation unit for estimating the clothing size of the presumed subject based on the biometric information acquired by the biometric acquisition unit and the multiple biometric information stored in the storage unit.

[0011] With this configuration, the size of the clothing of the presumed subject can be estimated based on the subject's biological information representing the subject's biological information. Therefore, with this configuration, it is easy to obtain a more suitable size of clothing for the wearer.

[0012] In the above-described clothing size acquisition system, the clothing size estimation unit can also estimate the clothing size corresponding to the biological information that is near the biological information of the subject among the multiple biological information stored in the storage unit as the estimated clothing size of the subject.

[0013] With this configuration, the size of the clothing of the presumed subject can be easily estimated based on the subject's biological information representing the presumed subject's biological information.

[0014] The above-mentioned clothing size acquisition system includes a suitability calculation unit, which calculates the suitability of the clothing size estimated by the clothing size estimation unit relative to the estimated subject.

[0015] This structure allows us to determine whether the clothing of the presumed size is suitable for the presumed individual.

[0016] In the above-mentioned clothing size acquisition system, the suitability calculation unit can also calculate the suitability based on the probability that the clothing size estimated by the clothing size estimation unit is the clothing size of the estimated subject, based on multiple biological information stored in the storage unit.

[0017] This structure makes it easy to determine whether the estimated size of clothing is appropriate.

[0018] In the above-mentioned clothing size acquisition system, the fit calculation unit can also calculate the probability based on the proportion or distribution of the clothing size established by the biological information in the multiple biological information stored in the storage unit, which is within a specified range based on the biological information of the subject.

[0019] This structure makes it easy to determine whether the estimated size of clothing is appropriate.

[0020] In the above-mentioned clothing size acquisition system, the fit calculation unit calculates the correction degree as the fit degree. The correction degree is the difference between the representative value of the bio-information in the clothing size estimated by the estimation unit and the bio-information of the subject, or the difference between the representative value of the size in the clothing size estimated by the estimation unit and the size obtained based on the bio-information of the subject.

[0021] This structure makes it easy to determine whether the estimated size of clothing is appropriate.

[0022] In the above-mentioned clothing size acquisition system, the fit calculation unit may calculate the probability that the clothing size estimated by the clothing size estimation unit is the clothing size of the estimated subject, based on multiple biometric information stored in the storage unit, and the fit calculation unit calculates the representative value based on the biometric information and the probability.

[0023] This structure allows for the calculation of a representative value based on the probability that the estimated clothing size is the same as the clothing size of the person being estimated, thus enabling a more accurate determination of whether the estimated clothing size is appropriate.

[0024] In the above-described clothing size acquisition system, the clothing size of the person being estimated, as estimated by the clothing size estimation unit, can also be displayed on the image display unit.

[0025] This structure allows the person being assessed to determine the appropriate size of clothing for themselves.

[0026] In the above-mentioned clothing size acquisition system, there may also be a size change period estimation unit, which estimates the period during which the size of the clothing of the estimated subject changes based on the previously acquired biological information of the subject and the newly acquired biological information of the subject.

[0027] Through this structure, the presumed subject can identify changes in their body shape and the appropriate size of clothing to match.

[0028] In the above-mentioned clothing size acquisition system, the clothing can also be the clothes of the presumed subject.

[0029] This design makes it easy to obtain a more suitable clothing size for the presumed subject.

[0030] In the above-mentioned clothing size acquisition system, the storage unit may store multiple biometric information corresponding to the clothing size as a database, and the database may be updated by adding new biometric information corresponding to the clothing size.

[0031] By using this structure to update the database sequentially, the accuracy of estimating the clothing size of the person being estimated can be improved.

[0032] In the aforementioned clothing size acquisition system, the subject's biometric information is measured by a body composition analyzer based on the bioimpedance measurement body of the presumed subject. The biometric information includes at least one of the following: fat percentage, fat mass, non-fat mass, muscle mass, visceral fat mass, visceral fat grade, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water percentage, BMI (Body Mass Index), intracellular fluid volume, and extracellular fluid volume.

[0033] This configuration allows for the estimation of clothing dimensions of a potential subject based on biological information calculated from bioimpedance.

[0034] One approach to clothing size acquisition involves a computer functioning as a clothing size estimation unit. This estimation unit estimates the clothing size of the person being estimated based on multiple corresponding biometric information entries established with respect to clothing size representing the size of clothing worn by the person being estimated, and the biometric information of the person being estimated obtained by a biometric information acquisition unit.

[0035] This design allows for easy acquisition of a more suitable garment size for the wearer.

[0036] A method for assisting in selecting clothing includes: a first step of estimating the clothing size of a customer based on multiple biometric information corresponding to clothing size representing the size of clothing worn by the customer and the customer's biometric information acquired by a biometric information acquisition unit; a second step of displaying the clothing size estimated in the first step on an information processing device in a store; and a third step of a store clerk confirming the clothing size displayed on the information processing device to assist the customer in selecting clothing.

[0037] This structure enables shop assistants who provide clothing to customers to identify customers who need assistance in selecting clothing, thus allowing them to work more efficiently.

[0038] Invention Effects

[0039] According to the present invention, it is possible to easily obtain a more suitable garment size for the wearer. Attached Figure Description

[0040] Figure 1 This is a diagram illustrating the clothing size acquisition system of the first embodiment.

[0041] Figure 2 This is a functional block diagram of the clothing size acquisition system according to the first embodiment.

[0042] Figure 3 This is a schematic diagram of the clothing size database of the first embodiment.

[0043] Figure 4 This is a flowchart of the method for obtaining clothing size according to the first embodiment.

[0044] Figure 5 This is a diagram illustrating the clothing size acquisition system according to the second embodiment.

[0045] Figure 6 This is a functional block diagram of the clothing size acquisition system according to the second embodiment.

[0046] Figure 7 This is a flowchart of the method for obtaining clothing size according to the second embodiment. Detailed Implementation

[0047] Hereinafter, embodiments will be described with reference to the accompanying drawings. It should be noted that the embodiments described below represent one example of implementing the present invention and are not intended to limit the invention to the specific configurations described below. In implementing the present invention, specific configurations corresponding to the embodiments may be appropriately adopted.

[0048] (First Implementation)

[0049] In this embodiment, clothing is used as an example of clothing, and the clothing size acquisition system is set as a system used in a clothing store. It should be noted that clothing can be, for example, shirts, jackets, pants, skirts, coats, and underwear, as long as it is worn on the upper body, lower body, or the whole body, without any particular limitation. Figure 1 This diagram illustrates the clothing size acquisition system of this embodiment. In this embodiment, the clothing size acquisition system 10 includes a measuring device 12, a store terminal 14 which serves as an information processing device, and a server 16.

[0050] The measuring device 12 is a body composition meter based on the bioimpedance measurement of the subject. In this embodiment, the measuring device 12 is installed in each clothing store and used by clothing purchasers (hereinafter referred to as "customers") to measure the customer's body composition. That is, the subject of this embodiment is the customer, the person to whom the estimated clothing size is estimated (described later).

[0051] The measuring device 12 of this embodiment includes a touch panel display 20 and a main body 30. The touch panel display 20 is located at the upper end of a support column erected from the main body 30. Furthermore, the main body 30 includes a platform 32 for the person being measured to sit on, a right handle 33R, and a left handle 33L. The person being measured stands barefoot on the platform 32, holding the right handle 33R with their right hand and the left handle 33L with their left hand, thus forming a measuring body. The detailed description of the measuring device 12 will be provided below.

[0052] The touch panel display 20 includes a display panel 21 such as a liquid crystal display panel, and an input device 22, such as a touch sensor integrated with the display panel 21, for receiving touch input. It should be noted that the input device 22 can also be a button, switch, or other input device separate from the display panel 21. The display panel 21 displays the measurement results based on the measuring device 12 and the estimated clothing size (hereinafter referred to as "clothing size estimated result"), which will be described in detail later.

[0053] The main body 30, in addition to the aforementioned mounting platform 32, right handle 33R, and left handle 33L, also includes a body composition measuring unit 31 and a weight measuring unit 34. The mounting platform 32 includes a right foot power electrode 321R, a right foot measuring electrode 322R, a left foot power electrode 321L, and a left foot measuring electrode 322L. Furthermore, the right handle 33R includes a right hand power electrode 331R and a right hand measuring electrode 332R, and the left handle 33L includes a left hand power electrode 331L and a left hand measuring electrode 332L.

[0054] The weight measuring unit 34 is equipped with a force sensor for measuring weight. The force sensor consists of a strain gauge of a metal component that deforms under load and a strain gauge attached to the strain gauge. When the user sits on the platform 32, the strain gauge of the force sensor flexes due to the user's load, and the strain gauge expands and contracts. The impedance value (output value) of the strain gauge changes according to its expansion and contraction. The weight measuring unit 31 calculates the weight based on the difference between the output value (zero point) of the force sensor when no load is applied and the output value when a load is applied. It should be noted that the configuration for measuring weight using the force sensor is the same as that of a general weighing scale.

[0055] Age, gender, and height are input into the body composition measurement unit 31 as the subject's biometric information. This biometric information is input to the body composition measurement unit 31 via the touch panel display 20. It should be noted that biometric information acquired by units of other devices can also be input into the body composition measurement unit 31. For example, the other device could be one that analyzes images of the subject captured by a camera to estimate the subject's height, age, gender, etc., and this estimation result could be input into the body composition measurement unit 31 as biometric information. Furthermore, in addition to height, age, and gender, other biometric information of the subject can also be input into the body composition measurement unit 31.

[0056] The body composition measurement unit 31 includes: a current supply function that allows a weak current of a specified frequency to flow from each energized electrode to a specified part of the body of the subject; a potential difference measurement function that measures the potential difference generated in the current path; and a bioimpedance calculation function that calculates the bioimpedance of the user's whole body and each body part based on the aforementioned values ​​of current and potential difference.

[0057] The bioimpedance measurements of the whole body and individual body parts of the subject, performed by the body composition measurement unit 31, are as follows.

[0058] (1) In the measurement of bioimpedance of the whole body, the left hand electrode 331L and the left foot electrode 321L are used to supply current. The potential difference between the left hand measuring electrode 332L that is in contact with the left hand and the left foot measuring electrode 322L that is in contact with the left foot is measured along the current path that flows through the left hand, left arm, chest, abdomen, left leg and left foot.

[0059] (2) In the measurement of bioimpedance of the right leg, the right hand electrode 331R and the right foot electrode 321R are used to supply current. The potential difference between the left foot measuring electrode 322L, which is in contact with the left foot, and the right foot measuring electrode 322R, which is in contact with the right foot, is measured along the current path that flows through the right hand, right arm, chest, abdomen, right leg and right foot.

[0060] (3) In the measurement of bioimpedance of the left leg, the left hand electrode 331L and the left foot electrode 321L are used to supply current. The potential difference between the left foot measuring electrode 322L, which is in contact with the left foot, and the right foot measuring electrode 322R, which is in contact with the right foot, is measured along the current path that flows through the left hand, left arm, chest, abdomen, left leg and left foot.

[0061] (4) In the measurement of bioimpedance of the right arm, the right hand electrode 331R and the right foot electrode 321R are used to supply current. The potential difference between the left hand measuring electrode 332L that is in contact with the left hand and the right hand measuring electrode 332R that is in contact with the right hand is measured along the current path that flows through the right hand, right arm, chest, abdomen, right leg and right foot.

[0062] (5) In the measurement of bioimpedance of the left arm, the left hand energized electrode 331L and the left foot energized electrode 321L are used to supply current. The potential difference between the left hand measuring electrode 332L that is in contact with the left hand and the right hand measuring electrode 332R that is in contact with the right hand is measured along the current path that flows through the left hand, left arm, chest, abdomen, left leg and left foot.

[0063] The body composition measurement unit 31 applies the input biological information of the subject, the weight measured by the weight measurement unit 34, and the calculated bioimpedances to a prescribed regression equation and performs calculations to calculate the body composition measurement values ​​for the whole body and individual body parts. The body composition measurement unit 31 calculates the following body composition measurement values: fat percentage, fat mass, non-fat mass, muscle mass, visceral fat mass, visceral fat grade, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water percentage, BMI, intracellular fluid volume, and extracellular fluid volume. The configuration related to the calculation of body composition measurement values ​​can also use the same configuration as a general body composition analyzer. It should be noted that, in the following description, the biological information of the subject input to the body composition measurement unit 31 and the body composition measurement values ​​calculated by the body composition measurement unit 31 are collectively referred to as subject biological information or body composition data.

[0064] Regarding the measuring device 12, it is preferable that the subject is barefoot during the measurement as described above. However, since the measuring device 12 in this embodiment is used by customers of the shop, it is not necessary for the subject to be barefoot while sitting on the main body 30. For example, the subject can be seated on the main body 30 while wearing socks or shoes. In this case, the bioimpedance measurement using the electrodes on the right and left legs to obtain the subject's bio-information is not performed. Thus, the measuring device 12 does not necessarily need to perform bioimpedance measurement using all the electrodes on the right hand, left hand, right leg, and left leg, but can measure bioimpedance using at least two electrodes on the right hand, left hand, right leg, and left leg.

[0065] In addition, the measuring device 12 has communication functions with other information processing devices such as the server 16, sending the measurement results obtained by the measuring device 12 to the server 16, or receiving clothing size estimation results from the server 16.

[0066] Next, the composition of the store terminal 14 and the server 16 will be explained.

[0067] The store terminal 14 is an information processing device that includes a touch panel display 15, a computer capable of executing applications, internal memory such as flash memory, and various connectors. Furthermore, the store terminal 14 includes a wireless communication device for connecting to the Internet, a short-range communication device for connecting to other nearby devices, and receives clothing size estimation results from the server 16, displaying these results on the touch panel display 15. It should be noted that the store terminal 14 is held by a store employee. As an example, it may be a portable information processing device such as a smartphone or tablet, but it is not limited to these; other information processing devices such as desktop or laptop computers may also be used.

[0068] Server 16 is an information processing device that includes a computer such as a CPU (Central Processing Unit) capable of executing programs, a storage device such as an HDD (Hard Disk Drive), a communication device for connecting to the Internet or an intranet, and various connectors. In this embodiment, server 16 can transmit and receive data with measuring device 12 and store terminal 14, estimate customer clothing sizes based on the biometric information received from measuring device 12, and send the clothing size estimation results to measuring device 12 and store terminal 14. It should be noted that server 16 can be installed in each store or in each designated area where multiple stores exist.

[0069] Figure 2 This is a functional block diagram of the clothing size acquisition system 10 according to this embodiment. The clothing size acquisition system 10 includes a storage unit 50, a body composition data acquisition unit 52, a clothing size estimation unit 54, a fit calculation unit 56, an estimation result sending unit 58, and a database update unit 60. It should be noted that, in this embodiment, as an example... Figure 2 The functions shown are implemented by the computer on server 16 executing the clothing size estimation program stored in storage unit 50. It should be noted that... Figure 2 Each component of the clothing size acquisition system 10 shown can also be implemented using separate hardware such as an ASIC (Application Specific Integrated Circuit). It should be noted that, in the following description, the object being measured by the measuring device 12 is referred to as the estimated object. The clothing size estimation program can be downloaded to the server 16 from a communication network, or it can be provided to the server 16 via a non-transitory recording medium.

[0070] The storage unit 50 stores multiple pieces of biometric information (body composition data) corresponding to the clothing size (size data) representing the size of the clothing worn by the estimated subject. Specifically, the storage unit 50 stores multiple pieces of body composition data corresponding to the size data as a size database 62.

[0071] Formulas (1) to (3) below represent the size database 62, where DB represents the database, BC represents the volume composition data, and CS represents the size data. Furthermore, n is an integer, and volume composition data and size data with the same n value are in a corresponding relationship. Thus, the size database 62 is a set of n combinations of volume composition data and size data.

[0072] [Formula 1]

[0073] DB=[[BC],[CS],...]…(1)

[0074] BC = [BC1, BC2, ... BC] n ]…(2)

[0075] CS = [CS1, CS2, ... CS] n ]…(3)

[0076] Figure 3 This is a schematic diagram representing the size database 62. As an example, in Figure 3 In the size database 62, clothing sizes are mapped to individual body composition data. It should be noted that, as an example, the size database 62 uses combinations of two body composition data elements, X and Y, as the composition data for each body. Figure 3 The values ​​of the constituent data in the middle are represented as (Xn, Yn). It should be noted that... Figure 3 The solid circle shown (X) O Y O The biological information of the object is acquired by the measuring device 12 and is not included in the size database 62.

[0077] Body composition data elements X and Y can be any two of, for example, fat percentage, fat mass, non-fat mass, muscle mass, visceral fat mass, visceral fat grade, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water percentage, BMI, intracellular fluid volume, and extracellular fluid volume. Furthermore, the size database 62 can be set according to, for example, the weight and height of each presumed subject. Moreover, the body composition data is not limited to a combination of two body composition data elements X and Y, but can use one body composition data element X or a combination of three or more body composition data elements X, Y, Z, etc., as long as the clothing size corresponds to each body composition data element. Furthermore, the body composition data elements can be any value that the presumed subject can input to the measuring device 12, or any other value that can be calculated based on the bioimpedance measured by the measuring device 12, or any other value.

[0078] As an example, the clothing sizes in this embodiment are marked with S (Small), M (Medium), L (Large), etc., but are not limited to these; other markings are also possible, as well as numerical values, ranges, or ratios used for estimating clothing sizes, such as waist circumference and chest circumference. Furthermore, clothing sizes can be, for example, Y, A, and AB, sizes that vary according to the wearer's body type, or patterns such as straight-leg, fitted, and boot-style clothing.

[0079] The body composition data acquisition unit 52 acquires subject biological information representing the body composition data of the presumed subject acquired by the measuring device 12 via a communication line.

[0080] The clothing size estimation unit 54 estimates the clothing size of the person being estimated based on the biological information of the person being estimated acquired by the body composition data acquisition unit 52 and multiple body composition data stored in the storage unit 50. In other words, the clothing size estimation unit 54 estimates the size data corresponding to the body composition data that has the strongest relationship with the body composition data of the person being estimated as the clothing size of the person being estimated in a multi-dimensional space with the body composition data as the axis.

[0081] As an example, the clothing size estimation unit 54 in this embodiment will compare the clothing size estimation unit with the biological information (Xn, Yn) of the multiple body composition data (Xn, Yn) stored in the storage unit 50, relative to the subject's biological information (Xn, Yn). O Y O The clothing size corresponding to the nearby body composition data is used to estimate the clothing size of the person being estimated. Therefore, the clothing size of the person being estimated can be easily estimated based on the biological information of the person being estimated, which represents the body composition data.

[0082] It should be noted that, as explained below, relative to the subject's biometric information (X... O Y OThe biometric data (Xn, Yn) of a nearby body are extracted from multiple body composition data (Xn, Yn) through a prescribed computational process. As an example, this computational process extracts biometric information (Xn) relative to the subject. O Y O The most recent body composition data (Xn, Yn). However, computational processing may not necessarily extract biological information relative to the object (Xn). O Y O The most recent body composition data (Xn, Yn). For example, it could also be body composition data (Xn, Yn) with inappropriate clothing size relative to the subject's biometric information (Xn, Yn). O Y O In the most recent case, the calculation process does not extract the component data (Xn, Yn) of this body.

[0083] The following describes an example of a method for estimating clothing size (calculation processing). In this embodiment, estimation methods (1) to (3) are listed, but the method for estimating clothing size is not limited to these.

[0084] (1) Estimation based on Euclidean distance

[0085] In estimation method (1), the size data corresponding to the body composition data with the smallest Euclidean distance to the subject's biological information is estimated as the subject's clothing size. The following formula (4) is an example of the formula for calculating Euclidean distance.

[0086] [Formula 2]

[0087] D i =∑ j |v ij -v oj |×w j …(4)

[0088] i: Data number in the size database

[0089] j: The number of the variable (axis) that constitutes the multidimensional coordinate system.

[0090] D i Similarity between data i and measurement data

[0091] v ij : The vector that constitutes the j-th variable of the data of the i-th individual

[0092] v oj : A vector of the j-th variable constituting the bodily composition data (biological information of the presumed subject) of the subject.

[0093] w j: The weight of the j-th variable. Without weights, w j =1

[0094] exist Figure 3 In the example, because the body composition data (X3, Y3) is relative to the object's biological information (X... O Y O Since the Euclidean distance is the smallest, the clothing size is assumed to be "S".

[0095] (2) Inference based on nearby data sets

[0096] In estimation method (2), the size data with the largest proportion in the neighborhood data set (hereinafter also referred to as "cluster") which is the set of body composition data near the subject's biological information is estimated as the estimated clothing size of the subject. When the number of data used as neighborhood is set to k, the neighborhood data set kDB is represented by the following formula (5). It should be noted that the method of determining the cluster is not particularly limited. For example, it can also be set as the body composition data included within a predetermined Euclidean distance from the subject's biological information.

[0097] [Formula 3]

[0098] kDB = [D1, D2, ... D k ]…(5)

[0099] Then, estimation method (2) estimates the most frequent size data among the size data included in formula (5) as the estimated clothing size of the subject. It should be noted that, in the case of k=1, relative to the subject's biometric information (X... O Y O The most recent size data D1 is assumed to be the clothing size of the person being assessed.

[0100] Furthermore, as shown in formula (6) below, the size data can also be weighted according to the Euclidean distance to the biological information of the subject. modify_x It is the number of clothing sizes x included in the kDB weighted Euclidean distance. x And the value obtained. Then, Count. modify_x The largest value of the size data is presumed to be the clothing size of the person being assessed.

[0101] [Formula 4]

[0102]

[0103] (3) Estimation based on density clusters

[0104] The maximal set of volume composition data in the volume composition data included in the size database 62 that satisfies the conditions expressed by the following formulas (7) to (9) is set as a cluster (a density-based cluster).

[0105] [Formula 5]

[0106] N ε (q): {p∈n|DB(p, q)≤ε}…(7)

[0107] p∈N ε (q)…(8)

[0108] N ε (q)≥MinPts…(9)

[0109] p, q: Any data in the size database

[0110] ε: Euclidean distance between data points p and q

[0111] N ε : The set of points within a distance ε

[0112] Furthermore, in the estimation method (3), the size data with the highest density in the cluster that includes the subject's biological information is estimated as the estimated size of the subject's clothing.

[0113] The clothing size estimated by the clothing size estimation unit 54 (hereinafter referred to as "estimated clothing size") is output to the suitability calculation unit 56.

[0114] The suitability calculation unit 56 calculates the suitability of the estimated clothing size relative to the estimated subject. The estimated clothing size is based on the subject's biometric information, derived from the body composition data; therefore, the estimation result may be unsuitable. Therefore, by calculating the suitability of the estimated clothing size using the suitability calculation unit 56, and by having the estimated subject (as a customer) or a store employee confirm the result, it can be determined whether the estimated clothing size is suitable for the estimated subject. Thus, the estimated subject can choose the most suitable clothing with their own assistance or the help of a store employee. It should be noted that the suitability calculation unit 56 in this embodiment includes a consistency probability calculation unit 64 and a correction calculation unit 66.

[0115] The consistency probability calculation unit 64 calculates the probability (hereinafter referred to as "consistency probability") that the estimated clothing size is the same as the estimated person's clothing size based on the multiple individual composition data stored in the storage unit 50, and uses this as the suitability. In other words, the consistency probability is an indicator of whether the estimated clothing size is suitable for the estimated person. It should be noted that the more suitable the estimated clothing size is for the estimated person, the higher the value of the consistency probability.

[0116] As an example, the consistency probability calculation unit 64 of this embodiment calculates the consistency probability based on the proportion or distribution of clothing sizes established in the multiple body composition data stored in the storage unit 50, which are within a specified range based on the subject's biometric information. Therefore, the suitability calculation unit 56 can easily determine whether the estimated clothing size is suitable.

[0117] The following describes examples of methods for calculating the uniformity probability. In this embodiment, the following calculation methods (1) and (2) are listed, but are not limited thereto.

[0118] (1) Calculate based on the proportion of size data included in the cluster.

[0119] Let N be the number of size data in the cluster to which the subject's biometric information belongs that are the same as the estimated clothing size. t Let N be the number of size data that differ from the estimated clothing size. f The consistency probability P is calculated using the following formula (10). t .

[0120] [Formula 6]

[0121]

[0122] exist Figure 3 Examples include the subject's biometric information (X). O Y O Clusters of clothing size “S” are shown by a single-dotted line. Furthermore, each cluster includes 7 body composition data points designated as size S and 2 body composition data points designated as size M, suggesting a probability of approximately 78% consistency for the clothing size “S”.

[0123] It should be noted that sometimes a cluster may include multiple clothing sizes that differ from the estimated clothing size. In such cases, the probability of the cluster being included is calculated for each different type of clothing size. Specifically, if the estimated clothing size is "M", body composition data with clothing size "S" and body composition data with clothing size "L" may also be included in the cluster. In such cases, the consistency probability calculation unit 64 also calculates the probability that the cluster includes clothing size "S" and the probability that it includes clothing size "L". Thus, based on the probability of clothing sizes that differ from the estimated clothing size, it is possible to determine whether the estimated subject's body shape is closer to size S (M size) or closer to size L (M size).

[0124] For example, in a cluster containing 10 individual biometric data points, if there are 7 biometric data points with clothing size "M", 1 biometric data point with clothing size "S", and 2 biometric data points with clothing size "L", the presumed clothing size of the individual belonging to this cluster is "M" with a 70% probability of agreement. Furthermore, the probability of clothing size "S" is 10%, and the probability of clothing size "L" is 20%. In this case, the presumed clothing size of the individual is estimated to be size M, which is close to size L. It should be noted that, for example, the probability of clothing size "S" could be negatively assigned and the probability of clothing size "L" could be positively assigned to identify the probability of each clothing size.

[0125] (2) Calculate based on the distribution differences of volume composition data for each size included in the cluster.

[0126] Let p be the probability distribution of the body composition data of the cluster to which the subject's biological information belongs, which is set to the same size as the estimated clothing size. t Let the probability distribution of the volume composition data of this cluster be p, and let the distribution difference KL(p) be the probability distribution of the cluster. t ||p) is expressed by the following formula (11). Furthermore, by using the difference KL(p) t The following formula (12) is used to calculate the uniformity probability P. t .

[0127] [Formula 7]

[0128]

[0129] BC k Volume composition data of variable (axis) k in a multidimensional space composed of volume composition data.

[0130] [Formula 8]

[0131]

[0132] On the other hand, the correction degree calculation unit 66 calculates the correction degree as the suitability. The correction degree is the difference between the representative value of the body composition data in the estimated clothing size and the subject's biological information, or the difference between the representative value of the size in the estimated clothing size (hereinafter referred to as "estimated size") and the size obtained based on the subject's biological information (hereinafter referred to as "subject's biological information size"). In other words, the correction degree is an index indicating how much the estimated subject's body shape differs from the representative body shape suitable for the estimated clothing size. Therefore, the suitability calculation unit 56 can easily determine whether the estimated clothing size is suitable.

[0133] Here, as an example, body composition data and representative values ​​of the estimated clothing size are pre-stored in a size database 62. Furthermore, the subject's biometric dimensions are obtained, for example, by retrieving body shape data corresponding to the subject's biometric information from a database that correspondingly stores body composition data and baseline body shape data.

[0134] Moreover, as an example, the degree of correction is expressed as the following formula (13).

[0135] [Formula 9]

[0136] M m，t =BC m，med -BC t …(13)

[0137] M m，t Correction degree of dimension m

[0138] BC m，med Representative values ​​of volumetric composition data in dimension m

[0139] BC t Biometric information of the target

[0140] Size m is an estimated garment size, which in this embodiment is any one of "S", "M", or "L". Alternatively, BC could be... m，med Let BC be the representative value of the estimated dimension in dimension m. t Set the size to the size of the object's biometric information.

[0141] It should be noted that when BC m,med Let BC be the representative value of the body composition data. t As an example, assuming the subject's biological information is used, the correction degree M is... m,t Expressed as a percentage (%), the higher the value, the more adjustment is required. Furthermore, when setting BC... m,med Set BC as the representative value of the estimated size. t As an example, given the size of the object's biometric information, the correction degree M... m,t It is represented by length (cm), and the larger the value, the more it is set to require correction.

[0142] Alternatively, if the calculated correction degree is above a predetermined threshold, the correction degree calculation unit 66 may attach a label indicating "correction needed" to the estimated clothing size; if the correction degree is below the threshold, the correction degree calculation unit 66 may attach a label indicating "no correction needed" to the estimated clothing size. When "correction needed" is selected, clothing selection assistance is provided by the salesperson as described later. Furthermore, the correction degree may be displayed on the touch panel display 20 of the measuring device 12, allowing the person being assessed to confirm it. After confirming the correction degree, the person being assessed may choose whether correction is needed via the touch panel display 20.

[0143] Furthermore, as mentioned above, the representative value of the estimated size is obtained from the size database 62, but is not limited thereto; the representative value of the estimated size can also be calculated based on the volume composition data and the aforementioned consistency probability. As a prior art technique, the representative value of the estimated size can also be calculated by using a predetermined function input volume composition data as a variable. However, this function is obtained through statistical methods and may include singular data from the statistics; therefore, the estimation accuracy of the representative value may decrease in the calculation using this function.

[0144] Therefore, by using the probability of consistency to weight statistically high and low-occurrence data to calculate a representative value for the estimated size, the accuracy of the estimated size can be improved. In other words, using the probability of consistency in calculating the representative value of the estimated size takes into account the degree of deviation between the estimated subject's body shape and the clothing size. More specifically, when the estimated clothing size is calculated to be "S", the lower the probability of consistency, the closer the estimated subject's body shape is to the clothing size "M". Therefore, by using the probability of consistency in calculating the representative value of the estimated size, this representative value is calculated to be a more appropriate value corresponding to the estimated subject, that is, a value close to the clothing size "M".

[0145] As an example of a method for calculating a representative value of an estimated size, there are examples where the consistency probability is used as a threshold, as shown in formulas (14) and (15) below, and different calculation formulas are used with this threshold as the boundary. Formulas (14) and (15) are examples of formulas for calculating a representative value of the arm size of clothing, L arm FAT is the length of the long axis of the arm. arm For arm fat mass, WEIGHT arm For the arm weight, these values ​​are pre-stored as averages in the size database 62 according to each garment size. That is, the uniformity probability P calculated by the uniformity probability calculation unit 64... t Given a predetermined probability of agreement, the representative value of the estimated size is calculated using formula (14), with a probability of agreement P. tIf the probability of agreement is less than the predetermined probability of agreement, the representative value of the estimated size is calculated using formula (15).

[0146] [Formula 10]

[0147] P t ≥X;f(L arm FAT arm WEIGHT arm (14)

[0148] P t <X; g(L) arm FAT arm WEIGHT arm (15)

[0149] Furthermore, as another example of a method for calculating the representative value of the estimated size, the uniformity probability P can also be increased as shown in the following formula (16). t As a variable of a function.

[0150] [Formula 11]

[0151] f(L arm FAT arm WEIGHT arm P t (16)

[0152] Thus, the consistency probability and correction degree calculated by the suitability calculation unit 56, along with the estimated clothing size, are output to the estimation result sending unit 58.

[0153] The estimation result sending unit 58 sends the estimated clothing size estimated by the clothing size estimation unit 54, the consistency probability calculated by the fit calculation unit 56, and the correction degree to the measuring device 12 and the store terminal 14 via the communication line.

[0154] Furthermore, the database update unit 60 updates the size database 62 by adding (registering) new body composition data corresponding to the size data. It should be noted that an information processing device capable of accessing the size database 62 is predetermined, and the combination of newly added body composition data and size data from this information processing device is input to the database update unit 60. Thus, the size database 62 is updated sequentially, improving the accuracy of the estimated clothing size for the estimated subject. It should be noted that, as an example, the update of the size database 62 is performed by the user (provider) of the clothing size acquisition system 10 service. It should also be noted that the size database 62 can delete registered combinations of body composition data and size data.

[0155] Figure 4This is a flowchart representing the process of clothing size estimation (clothing size estimation program) executed by server 16.

[0156] First, in step S100, the body composition data acquisition unit 52 determines whether the subject's biological information has been input from the measuring device 12. If the determination is positive, it is set that the subject's biological information has been acquired, and the process proceeds to step S102. If the determination is negative, the process remains in a waiting state until the subject's biological information is input.

[0157] It should be noted that when the measuring device 12 sends the subject's biometric information to the server 16, the subject selects to perform clothing size estimation processing via the touch panel display 20 of the measuring device 12. When performing clothing size estimation processing, the subject, who is a customer of the store, enters identification information such as their store membership number and their name to identify the customer.

[0158] In step S102, based on the body composition data included in the size database 62 and the obtained biological information of the subject, the clothing size estimation unit 54 estimates the clothing size of the subject.

[0159] In the next step S104, the fit calculation unit 56 calculates the consistency probability and correction degree to determine the fit of the estimated clothing size relative to the estimated subject.

[0160] In the next step S106, the estimation result sending unit 58 sends the estimated clothing size, consistency probability, and correction degree to the measuring device 12 and the store terminal 14. The estimated clothing size, consistency probability, and correction degree are displayed on the touch panel display 20 of the measuring device 12 and the touch panel display 15 of the store terminal 14.

[0161] Therefore, customers can confirm their clothing size without relying on store clerks. Furthermore, store clerks also confirm the customer's estimated clothing size, consistency probability, and correction degree, allowing them to assist customers in selecting clothing as needed (hereinafter referred to as "clothing selection assistance"). It should be noted that while displaying the estimated clothing size on the store terminal 14, it also displays the time the customer took the measurement based on the measuring device 12, the identification information entered by the customer, etc. Thus, store clerks can identify customers who have made an estimated clothing size determination.

[0162] Furthermore, the transmission of estimated clothing sizes to the store terminal 14 is not always continuous; for example, it can be done only when any of the following conditions are met. Therefore, sales staff can assist customers with clothing selection only when the customer deems it necessary. Moreover, this system can be used even by customers who do not wish their body composition data or estimated clothing sizes to be known by sales staff or the store.

[0163] (1) The case where a predetermined time T1 has elapsed after the customer finishes the measurement based on the measuring device 12.

[0164] (2) The case where the probability of agreement is less than the specified value P

[0165] (3) Cases where the correction degree is above the specified value M

[0166] (4) When the customer selects "Needs to be corrected" or selects "Select auxiliary request" from the store clerk.

[0167] (5) When the customer's stay in the store exceeds the specified time T2.

[0168] (6) When the customer selected "Send estimated clothing size"

[0169] Conditions (1) and (5) indicate situations where the customer is considered unsure about purchasing clothing. It should be noted that the determination of the specified times T1 and T2 is made, for example, by using cameras installed in the store to identify the customer's face and calculating the elapsed time after the customer finishes the measurement and the elapsed time after entering the store. Furthermore, for conditions (2) and (3), the estimated clothing size may not be suitable for the customer; in this case, assistance from the store clerk is required. Condition (4) indicates a situation where the customer feels the estimated clothing size may be unsuitable. Condition (6) indicates a situation where, regardless of whether the estimated clothing size is suitable, the customer wants to discuss purchasing the clothing with the store clerk. It should be noted that if the customer selects "send estimated clothing size" and conditions (1) to (5) are met, the estimated clothing size can also be sent to the store terminal 14.

[0170] It should be noted that the estimated clothing size estimated by the clothing size estimation unit 54, the consistency probability calculated by the fit calculation unit 56, and the correction degree can be output through the information processing device. For example, they can also be printed onto the recording medium by a printing device connected to the measuring device 12 or the store terminal 14. Alternatively, only the estimated clothing size can be sent to the measuring device 12, while the estimated clothing size, consistency probability, and correction degree can be sent to the store terminal 14.

[0171] As explained above, the clothing size acquisition system 10 of this embodiment estimates the clothing size of the estimated subject based on the subject's biological information representing the subject's body composition data, and determines whether the estimated clothing size is suitable for the estimated subject. Therefore, with respect to the clothing size acquisition system 10 of this embodiment, customers who are purchasing clothing can easily obtain the clothing size that is suitable for them.

[0172] It should be noted that the size database 62 in this embodiment can also be multiple. This is because, depending on the manufacturer, brand, etc., clothing size markings may differ, or even if the markings are the same as other manufacturers, the actual size of the clothing may vary slightly. Therefore, the size database 62 can also be set according to the manufacturer, brand, and fashion category of each garment. In this case, when a person, presumably a customer, performs a measurement based on the measuring device 12, the names of the manufacturers and brands of the clothing sold in the store are displayed on the touch panel display 20. Then, the person presumably selects the manufacturer and brand of the clothing they wish to purchase, causing the clothing size acquisition system 10 to perform clothing size estimation processing. Thus, the clothing size acquisition system 10 uses the size database 62 corresponding to the selected manufacturer and brand to perform clothing size estimation processing.

[0173] Furthermore, the size database 62 can also be set up for each store. In this case, store staff can also generate and update the size database 62 via the store terminal 14. Specifically, only clothing from manufacturers and brands sold in the store will be registered in the size database 62, while clothing from manufacturers and brands that are no longer sold or have no inventory will be deleted from the size database 62.

[0174] In addition, the clothing size acquisition system 10, which has a size database 62 for each manufacturer and brand, can also present clothing from recommended manufacturers and brands along with the estimated clothing size to the presumed subject based on the subject's biometric information and past purchase history.

[0175] Furthermore, in this embodiment, the method by which the server 16 performs the clothing size estimation process has been described, but it is not limited to this; the measuring device 12 may also have... Figure 2 The function shown performs clothing size estimation processing. In this case, for example, the measuring device 12 and the store terminal 14 can send and receive data via short-range communication such as Bluetooth (registered trademark), and the estimated clothing size and fit calculated by the measuring device 12 are sent from the measuring device 12 to the store terminal 14. On the other hand, the server 16 stores the size database 62 and has a database update unit 60, which updates the size database 62 sequentially. Then, the measuring device 12 obtains and stores the new size database 62 from the server 16 via the store terminal 14.

[0176] (Second Implementation)

[0177] The second embodiment will now be described. The first embodiment described above involved installing the measuring device 12 in a shop; in this embodiment, the measuring device 12 will be installed in the home of the person being estimated.

[0178] Figure 5 This is a simplified structural diagram of the clothing size acquisition system 10 according to this embodiment. It should be noted that... Figure 5 In and Figure 1 The same components are given the same reference numerals and their descriptions are omitted. In this embodiment, as an example, a simple input / output unit 35 for displaying power on / off, function switching, and measurement results is provided on the main body 30. Furthermore, the information processing device (hereinafter referred to as "user terminal") 18 held by the presumed subject, such as a smartphone, can transmit and receive data with the measuring device 12 via short-range communication, sending the subject's biometric information generated by the measuring device 12 to the user terminal 18. Then, after the presumed subject inputs the clothing size estimation processing via the user terminal 18, the measured presumed subject's biometric information is sent to the server 16, where clothing size estimation processing is performed. The estimated clothing size calculated by the server 16 is sent to the user terminal 18 and displayed on the touch panel display 19 of the user terminal 18.

[0179] Figure 6 This is a functional block diagram illustrating the electrical configuration of the garment size acquisition system 10 according to this embodiment. It should be noted that... Figure 6 In and Figure 2 The same function blocks are given the same reference numerals and their descriptions are omitted.

[0180] The clothing size acquisition system 10 of this embodiment includes a user database 68 in the storage unit 50. The user database 68 is configured for each presumed subject, storing the estimation results of past clothing size estimation processes performed on the presumed subject, along with the subject's biometric information and the date. Therefore, the body composition data acquisition unit 52 stores the subject's biometric information in the user database 68 each time it acquires the subject's biometric information. Furthermore, the clothing size estimation unit 54 also stores the estimated clothing size in the user database 68 each time it estimates the clothing size, establishing a correspondence with the subject's biometric information used for estimation.

[0181] Furthermore, the clothing size acquisition system 10 of this embodiment includes a size change period estimation unit 70. The size change period estimation unit 70 estimates the period during which the clothing size of the estimated subject will change (hereinafter referred to as the "size change period") based on previously acquired subject biometric information and newly acquired subject biometric information. In other words, the size change period estimation unit 70 estimates the timing of clothing size changes based on the changing trends of the estimated subject's body composition data. That is, the size change period is an indicator of changes in the estimated subject's body shape, and the estimated subject can confirm their own body shape changes by confirming the size change period.

[0182] The size change period estimation unit 70 estimates, for example, the period when the clothing size of the estimated subject will change in the future by extrapolating an approximation line based on previously obtained subject biometric information and newly obtained subject biometric information. Then, the estimated size change period is output to the estimation result sending unit 58.

[0183] The estimation result sending unit 58 sends the period of size change along with the estimated clothing size to the user terminal 18.

[0184] Figure 7 This is a flowchart illustrating the process of clothing size estimation (clothing size estimation procedure) executed by the server 16 of this embodiment.

[0185] First, in step S200, the body composition data acquisition unit 52 determines whether the subject's biological information generated by the measuring device 12 has been input from the user terminal 18. If the determination is positive, it is set that the subject's biological information has been acquired, and the process proceeds to step S202. If the determination is negative, the process remains in a waiting state until the subject's biological information is input.

[0186] In step S202, the body composition data acquisition unit 52 causes the user database 68 to store the acquired biological information of the target.

[0187] In step S204, based on the body composition data included in the size database 62 and the obtained biological information of the subject, the clothing size estimation unit 54 estimates the clothing size of the subject.

[0188] In the next step S206, the fit calculation unit 56 calculates the consistency probability and correction degree to determine the fit of the estimated clothing size relative to the estimated subject.

[0189] In the next step S208, the size change period estimation unit 70 estimates the size change period.

[0190] In the next step S210, the estimation result sending unit 58 sends the estimated clothing size, consistency probability, correction degree, and period of size change to the user terminal 18 of the person being estimated. As a result, the estimated clothing size, consistency probability, correction degree, and period of size change are displayed on the touch panel display 19 of the user terminal 18. Therefore, the person being estimated can identify the clothing size that suits them and, if the estimated clothing size changes due to changes in body shape, can identify the period of change.

[0191] It should be noted that, for example, if the clothing size of the person presumed to be the subject of the presumption does not change within a specified period (e.g., within six months), the period of size change will be displayed as "No change in clothing size". In other words, if the clothing size changes within the aforementioned specified period, the period of change will be displayed.

[0192] Furthermore, the clothing size acquisition system 10 of this embodiment can also send (notify) the estimated clothing size of the estimated subject and the period of size change to the information processing device of the store pre-registered by the estimated subject. As a result, the store clerk can provide more appropriate clothing selection assistance without measuring the estimated subject's body size when the estimated subject comes to the store.

[0193] It should be noted that the transmission of estimated clothing size, size change period, etc. to the store's information processing device can also be in the case of any of the following conditions being met.

[0194] (1) The probability that the estimated clothing size of the person being estimated last time or the actual clothing size purchased is different from the new estimated clothing size, and the probability that the new estimated clothing size matches is greater than or equal to the specified value P.

[0195] (2) Input values ​​such as height and waist circumference of the subject at the last measurement, and the subject's biometric information, are used to determine the extent to which changes in these values ​​necessitate a change in clothing size.

[0196] The present invention has been described above using the embodiments described above, but the scope of the present invention is not limited to the scope described in the embodiments. Various changes or modifications can be made to the embodiments described above, and such changes or modifications are also included within the scope of the present invention. Furthermore, the configurations of the garment size acquisition system 10 of the first and second embodiments described above can also be appropriately combined to implement the invention.

[0197] For example, in the above embodiments, the method of using clothing as clothing has been described, but the present invention is not limited thereto. The clothing can be any item worn by the presumed subject, and can also be socks, gloves, shoes, hats, ski boots, snowboard boots, or other clothing.

[0198] Furthermore, the clothing size acquisition system 10 can also include a unit that provides feedback on whether the estimated clothing size is appropriate and the calculated probability of consistency. Thus, the estimated subject's biometric information and the clothing size deemed suitable by the estimated subject are registered in the size database 62. It should be noted that the feedback information can also include information about clothing actually tried on or purchased by the estimated subject (e.g., manufacturer, brand, model, design, etc.).

[0199] Furthermore, while the above embodiment describes the method of performing clothing size estimation processing on the server 16 or the measuring device 12, it is also possible for the store terminal 14 or the user terminal 18 to perform the clothing size estimation processing. In this case, the store terminal 14 or the user terminal 18 receives the subject's biometric information from the measuring device 12 and performs clothing size estimation processing based on the subject's biometric information. It should be noted that the size database 62 is appropriately downloaded from the server 16 to the store terminal 14 or the user terminal 18 and stored thereon. It should also be noted that in the second embodiment, the user database 68 may be stored on the user terminal 18 instead of the server 16.

[0200] Furthermore, in the above embodiment, in the size database 62, size data is established to correspond to each of the multiple body composition data. However, it is also possible to further establish a correspondence between design data related to clothing design, including at least one element such as color and pattern, and each body composition data. As an example, it is conceivable that design data suitable for clothing based on body composition estimated from the body composition as biological information of the subject is established to correspond to each of the multiple body composition data along with the size data. Specifically, for example, for body composition data where the estimated body shape is fat, a shrinking color is established as a color (design data), and for body composition data where the estimated body shape is fat, stripes are established as a pattern (design data).

[0201] Furthermore, the design data and the estimated dimensional data are displayed together on the touch panel display 20 of the measuring device 12, thereby presenting them to the estimated target. It should be noted that multiple design data can also be associated with a single component data, and one or more design data can also be presented to the estimated target based on the estimated target's past purchase history.

[0202] Furthermore, in the above embodiment, the method by which the clothing size estimation unit 54 estimates the clothing size has been described, but it is not limited thereto. The clothing size estimation unit 54 may also estimate the design of the clothing based on the biological information of the person being estimated, using the same method as the method described above for estimating the clothing size of the person being estimated.

[0203] In this case, the storage unit 50 stores a corresponding database (hereinafter referred to as the "design database") for each of the design data and the data of multiple body components. Furthermore, the clothing size estimation unit 54 estimates the design of the clothing for the estimated subject based on the subject's biometric information and the design database, for example, by using the above-mentioned (1) estimation based on Euclidean distance, (2) estimation based on nearby data groups, and (3) estimation based on density clusters.

[0204] Then, the estimated design data is displayed on the touch panel display 20 of the measuring device 12, thereby presenting it to the estimated target. It should be noted that there can be multiple estimated design data as data of the estimated target, or one or more design data can be presented to the estimated target based on the estimated target's past purchase history.

[0205] Furthermore, in this case, the suitability calculation unit 56 can also calculate whether the design of the estimated clothing is suitable for the estimated subject using the same method as described above for calculating whether the clothing size estimated by the clothing size estimation unit 54 is suitable for the estimated subject. Of course, the suitability calculation unit 56 may also calculate only the consistency probability and the correction degree mentioned above.

[0206] Explanation of reference numerals in the attached figures:

[0207] 10: Clothing size acquisition system;

[0208] 12: Measuring device;

[0209] 50: Storage section (storage unit);

[0210] 52: Body composition data acquisition unit (bioinformatics acquisition unit);

[0211] 54: Clothing size estimation section (clothing size estimation unit);

[0212] 56: Suitability Calculation Unit (Suitability Calculation Section);

[0213] 62: Size Database (Database);

[0214] 70: Dimensional change period estimation section (dimensional change period estimation unit).

Claims

1. A system for obtaining clothing size, comprising: The bioinformation acquisition unit acquires the bioinformation of the presumed object; The storage unit stores multiple biometric information corresponding to the size of clothing worn by the presumed subject; as well as The clothing size estimation unit estimates the clothing size of the person being estimated based on the biological information of the subject acquired by the biological information acquisition unit and multiple pieces of biological information stored in the storage unit. The subject's biological information is measured by a biometric analyzer based on the bioimpedance measurement body of the presumed subject. The bioinformation refers to at least one of the following: fat percentage, fat mass, non-fat mass, muscle mass, visceral fat mass, visceral fat grade, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water percentage, BMI, intracellular fluid volume, and extracellular fluid volume. The clothing size estimation unit estimates the clothing size of the person being estimated as the clothing size of the person being estimated, based on the clothing size corresponding to the biological information that is near the biological information of the person being estimated from among the multiple biological information stored in the storage unit. The clothing size acquisition system further includes: a fit calculation unit, which calculates the fit of the clothing size estimated by the clothing size estimation unit relative to the estimated subject. The suitability calculation unit calculates the correction degree as the suitability degree, which is the difference between the representative value of the bio-information in the clothing size estimated by the clothing size estimation unit and the biological information of the subject, or the difference between the representative value of the size in the clothing size estimated by the clothing size estimation unit and the size obtained based on the biological information of the subject.

2. The garment size acquisition system according to claim 1, wherein, The clothing size estimation unit extracts the biological information that is nearby to the biological information of the subject from the multiple biological information stored in the storage unit based on Euclidean distance, nearby data groups or density clusters, and estimates the clothing size corresponding to the extracted biological information as the estimated clothing size of the subject.

3. The garment size acquisition system according to claim 1, wherein, The suitability calculation unit calculates the probability that the clothing size estimated by the clothing size estimation unit is the clothing size of the person being estimated, based on multiple pieces of biometric information stored in the storage unit. The suitability calculation unit calculates the representative value based on the biological information and the probability.

4. The garment size acquisition system according to any one of claims 1 to 3, wherein, The clothing size of the person being estimated, as estimated by the clothing size estimation unit, is displayed on the image display unit.

5. The garment size acquisition system according to claim 1, comprising: A size change period estimation unit estimates the period of size change of the clothing of the presumed subject based on previously acquired biological information of the subject and newly acquired biological information of the subject.

6. The garment size acquisition system according to any one of claims 1 to 3 and 5, wherein, The clothing worn is the clothes of the presumed subject.

7. The garment size acquisition system according to any one of claims 1 to 3 and 5, wherein, The storage unit stores multiple biometric information entries, each corresponding to the size of the garment, as a database. The database is updated by adding new biometric information corresponding to the size of the clothing.

8. A garment size acquisition program product, comprising a garment size acquisition program, wherein, The clothing size acquisition program enables the computer to function as a clothing size estimation unit. The clothing size estimation unit estimates the clothing size of the person being estimated based on multiple biometric information stored in a storage unit corresponding to the clothing size representing the size of the clothing worn by the person being estimated, and the person's biometric information acquired by the biometric information acquisition unit, which serves as the biometric information of the person being estimated. The subject's biological information is measured by a biometric analyzer based on the bioimpedance measurement body of the presumed subject. The bioinformation refers to at least one of the following: fat percentage, fat mass, non-fat mass, muscle mass, visceral fat mass, visceral fat grade, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water percentage, BMI, intracellular fluid volume, and extracellular fluid volume. The clothing size estimation unit estimates the clothing size of the person being estimated as the clothing size of the person being estimated, based on the clothing size corresponding to the biological information that is near the biological information of the person being estimated from among the multiple biological information stored in the storage unit. The clothing size acquisition program also enables the computer to function as a fit calculation unit. The fit calculation unit calculates the fit of the clothing size estimated by the clothing size estimation unit relative to the estimated subject. The suitability calculation unit calculates the correction degree as the suitability degree, which is the difference between the representative value of the bio-information in the clothing size estimated by the clothing size estimation unit and the biological information of the subject, or the difference between the representative value of the size in the clothing size estimated by the clothing size estimation unit and the size obtained based on the biological information of the subject.

9. A method for assisting in selecting clothing, comprising: The first step involves estimating the size of the customer's clothing based on multiple biometric information stored in a storage unit that corresponds to the size of the clothing worn by the customer, and the biometric information of the object of the customer's biometric information obtained by the biometric information acquisition unit. The second step involves the store's information processing device outputting the size of the garment estimated through the first step. as well as The third step involves the salesperson confirming the clothing size output by the information processing device to assist the customer in selecting the appropriate clothing. The subject's biometric information is measured by a biometric analyzer based on the customer's bioimpedance measurements. The bioinformation refers to at least one of the following: fat percentage, fat mass, non-fat mass, muscle mass, visceral fat mass, visceral fat grade, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water percentage, BMI, intracellular fluid volume, and extracellular fluid volume. In the first step, the clothing size corresponding to the biometric information that is near the subject's biometric information among the multiple biometric information stored in the storage unit is estimated as the customer's clothing size. The clothing selection assistance method also has the following features: The fourth step involves calculating the fit of the clothing size estimated in the first step relative to the customer. In the fourth step, a correction degree is calculated as the fit degree, which is the difference between the representative value of the biometric information in the clothing size estimated in the first step and the biometric information of the subject, or the difference between the representative value of the size in the clothing size estimated in the first step and the size obtained based on the biometric information of the subject.

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