Chair Data Processing Device

Abstract

To provide a sitting posture data processing device, a sitting posture data processing system, a chair manufacturing device, a chair manufacturing method, a computer program, and a chair data processing device that can display, select, manufacture, etc., a chair that suits the body of a user who desires a chair. [Solution] The sitting posture data processing device includes an imaging data acquisition unit that acquires imaging data relating to the body surface shape of at least a portion of the human body, a generation unit that generates sitting posture data indicating the sitting posture of the human body based on the imaging data acquired by the imaging data acquisition unit, and an output unit that outputs chair information to a display unit based on the sitting posture data generated by the generation unit.

Description

[Technical Field]

[0001] The present technology relates to a sitting posture data processing device, a sitting posture data processing system, a chair manufacturing device, a chair manufacturing method, a computer program, and a chair data processing device that generate sitting posture data indicating the sitting posture of a human body from imaging data of the human body, and perform display, selection, manufacturing, etc. of a chair based on the generated sitting posture data. [Background technology]

[0002] In order to determine the dimensions of a wheelchair, a body dimension measuring device has been proposed that measures the body dimensions of a person who wishes to use a wheelchair. The body dimension measuring device includes a chair and multiple sensors. The person sits in the chair. The dimensions of each part of the person's body are detected by each sensor. The wheelchair is manufactured based on the detected dimensions, so that a wheelchair optimal for the person can be provided (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-45403 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the body dimension measuring device is large and requires a dedicated chair and multiple sensors, so the person being measured must move to the location where the body dimension measuring device is installed.

[0005] The present disclosure has been made in consideration of the above circumstances, and aims to provide a sitting posture data processing device, a sitting posture data processing system, a chair manufacturing device, a chair manufacturing method, a computer program, and a chair data processing device that can display, select, or manufacture a chair that suits the user's body, to a user who desires a chair. [Means for solving the problem]

[0006] A sitting posture data processing device according to one embodiment of the present disclosure includes an imaging data acquisition unit that acquires imaging data relating to the body surface shape of at least a portion of a human body, a generation unit that generates sitting posture data indicating the sitting posture of the human body based on the imaging data acquired by the imaging data acquisition unit, and an output unit that outputs chair information to a display unit based on the sitting posture data generated by the generation unit.

[0007] In the present disclosure, sitting posture data is generated based on imaging data relating to the body surface shape of at least a portion of the human body. Chair information is displayed based on the generated sitting posture data. A user can obtain information about a chair that suits their body simply by imaging their own body.

[0008] A sitting posture data processing device according to one embodiment of the present disclosure includes a similarity calculation unit that calculates the similarity between the imaging data acquired by the imaging data acquisition unit and each of a plurality of different accumulated data that are stored in advance and indicate the overall body surface shape of the human body, and a selection unit that selects at least one of the accumulated data in accordance with the similarity calculated by the similarity calculation unit, and the generation unit generates sitting posture data that indicates the sitting posture of the human body based on the selected accumulated data.

[0009] In the present disclosure, imaging data is compared with multiple different stored data showing the overall body surface shape of the human body, at least one stored data with a high degree of similarity is selected, and data showing the sitting posture is generated based on the selected stored data.

[0010] In the sitting posture data processing device according to an embodiment of the present disclosure, the imaging data is data relating to the shape of at least a part of the body surface of the human body in a standing or sitting position.

[0011] In the present disclosure, a user can choose to have their body imaged in either a standing or sitting position.

[0012] A sitting posture data processing device according to one embodiment of the present disclosure includes a human body information acquisition unit that acquires human body information indicating gender, age, height, weight, or body type, and the similarity calculation unit calculates the similarity based on the human body information acquired by the human body information acquisition unit.

[0013] In the present disclosure, the selection unit can select stored data having human body information similar to the human body information of the user.

[0014] A sitting posture data processing device according to one embodiment of the present disclosure includes a type acquisition unit that acquires a type of chair according to a purpose of use, and a design information calculation unit that calculates design information including dimensions of the chair based on the sitting posture data generated by the generation unit and the type of chair acquired by the type acquisition unit, and the output unit outputs product information of at least one chair to the display unit based on the design information calculated by the design information calculation unit.

[0015] In the present disclosure, for example, the selection unit compares the human body information of the user with the human body information related to the stored data, and selects the stored data whose human body information is more similar to the user's body information.

[0016] A sitting posture data processing device according to an embodiment of the present disclosure includes a receiving unit that receives a selection of one piece of product information from the product information output to the display unit.

[0017] In the present disclosure, for example, based on an operation by a user, any one piece of product information is selected from the product information of at least one chair. The selected product information is checked against, for example, inventory data of chairs to confirm whether the product information is in stock.

[0018] A sitting posture data processing system according to one embodiment of the present disclosure includes an imaging unit that images the body surface shape of at least a portion of a human body, an imaging data acquisition unit that acquires imaging data from the imaging unit, a generation unit that generates sitting posture data indicating the sitting posture of the human body based on the imaging data acquired by the imaging data acquisition unit, an output unit that outputs chair information based on the sitting posture data generated by the generation unit, and a display unit that displays the chair information output from the output unit.

[0019] In the present disclosure, sitting posture data is generated based on imaging data relating to the body surface shape of at least a portion of the human body. Chair information is displayed based on the generated sitting posture data. A chair user can obtain information about a chair that suits the user's body simply by imaging their own body.

[0020] A chair manufacturing device according to an embodiment of the present disclosure includes: an imaging data acquisition unit that acquires imaging data relating to a body surface shape of at least a part of a human body; a generation unit that generates sitting posture data indicating a sitting posture of the human body based on the imaging data acquired by the imaging data acquisition unit; a type acquisition unit that acquires a type of chair according to a purpose of use; and a design unit that generates a chair including dimensions based on the sitting posture data generated by the generation unit and the type of chair acquired by the type acquisition unit. The apparatus includes a design information calculation unit that calculates information, and a manufacturing unit that manufactures chairs based on the design information calculated by the design information calculation unit.

[0021] In the present disclosure, the manufacturing department manufactures a chair that fits the user's body based on the design information, i.e., a custom-made chair is manufactured.

[0022] A method for manufacturing a chair according to one embodiment of the present disclosure includes acquiring imaging data relating to the body surface shape of at least a portion of a human body, generating sitting posture data indicating the sitting posture of the human body based on the acquired imaging data, acquiring a type of chair according to the intended use, calculating design information including the dimensions of the chair based on the generated sitting posture data and the acquired type of chair, and manufacturing a chair based on the calculated design information.

[0023] In the present disclosure, the manufacturing department manufactures a chair that fits the user's body based on the design information, i.e., a custom-made chair is manufactured.

[0024] A computer program according to one embodiment of the present disclosure causes a computer to execute a process of acquiring imaging data relating to the body surface shape of at least a portion of a human body, generating sitting posture data indicating the sitting posture of the human body based on the acquired imaging data, and outputting information about a chair corresponding to the sitting posture data to a display unit.

[0025] In the present disclosure, sitting posture data is generated based on imaging data relating to the body surface shape of at least a portion of the human body. Chair information is displayed based on the generated sitting posture data. A chair user can obtain information about a chair that suits the user's body simply by imaging their own body.

[0026] A chair data processing device according to one embodiment of the present disclosure includes an imaging data acquisition unit that acquires imaging data relating to the body surface shape of at least a portion of a human body; a human body information acquisition unit that acquires human body information indicating gender, height, weight, or body type; an information acquisition unit that uses chair product information as training data and inputs the imaging data acquired by the imaging data acquisition unit and the human body information acquired by the human body information acquisition unit into a learning model that outputs chair product information when imaging data and human body information are input, to acquire the chair product information; and an output unit that outputs the chair product information acquired by the information acquisition unit to a display unit.

[0027] In the present disclosure, product information for a chair is displayed based on image data relating to the body surface shape of at least a portion of a human body and human body information. A user of the chair can obtain product information for a chair that fits the user's body simply by taking an image of their own body. [Effects of the Invention]

[0028] In a sitting posture data processing device, sitting posture data processing system, chair manufacturing device, chair manufacturing method, computer program, and chair data processing device according to an embodiment of the present disclosure, sitting posture data is generated based on imaging data relating to the body surface shape of at least a portion of a human body. Chair information is displayed based on the generated sitting posture data. A user can obtain information about a chair that suits their body simply by imaging their own body. [Brief explanation of the drawings]

[0029] [Figure 1] 1 is a block diagram of a sitting posture data processing system according to a first embodiment. [Figure 2] FIG. 10 is an explanatory diagram illustrating acquisition of imaging data by a terminal device. [Figure 3] 10 is an explanatory diagram illustrating the calculation of the similarity between imaging data and a plurality of stored data; FIG. [Figure 4] FIG. 10 is an explanatory diagram illustrating information included in sitting posture data. [Figure 5] 10 is a flowchart illustrating information processing by a data processing device. [Figure 6] FIG. 2 is an explanatory diagram illustrating design information. [Figure 7] FIG. 10 is a block diagram of a chair manufacturing apparatus according to a second embodiment. [Figure 8] FIG. 11 is a schematic diagram showing an example of a learning model according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0030] (Embodiment 1) The present invention will be described below with reference to the drawings showing a sitting posture data processing system 1 according to a first embodiment. FIG. 1 is a block diagram of the sitting posture data processing system 1. The sitting posture data processing system 1 comprises a data processing device 2, a terminal device 3, and a search device 4. The data processing device 2, the terminal device 3, and the search device 4 are configured to be able to communicate via a network. The data processing device 2 comprises a control unit 2a, a RAM 2b, a storage unit 2c, and a communication unit 2d. The control unit 2a, RAM 2b, storage unit 2c, and communication unit 2d are connected to each other via a bus.

[0031] The control unit 2a includes, for example, a CPU. Note that a logic circuit, for example, an FPGA, may be used instead of the CPU. Wired or wireless communication is performed between the data processing device 2 and the terminal device 3 and search device 4 via the communication unit 2d.

[0032] The terminal device 3 includes a display unit 3a, an operation unit 3b, an imaging unit 3c, and a communication unit 3d. The terminal device 3 is, for example, a personal computer, a smartphone, or a tablet terminal. The display unit 3a has a display screen. The operation unit 3b has a keyboard, a mouse, a touch panel, or the like. Wired or wireless communication is performed between the terminal device 3 and the data processing device 2 via the communication unit 3d.

[0033] FIG. 2 is an explanatory diagram for explaining acquisition of imaging data by the terminal device 3. The imaging unit 3c of the terminal device 3 includes, for example, a camera. Note that a 3D scanner may be used instead of the imaging unit 3c of the terminal device 3. When a 3D scanner is used, the accuracy of imaging the body surface can be improved compared to when a camera is used.

[0034] The imaging unit 3c captures an image of at least a portion of the user (human body). For example, the upper body, torso, lower body, or entire body is captured. The imaging unit 3c acquires imaging data relating to at least a portion of the body surface shape of the user in a standing position. Note that in FIG. 2, the user is in a standing position, but the user may be in a sitting or lying position, and the imaging unit 3c may acquire imaging data relating to at least a portion of the body surface shape in a sitting or lying position. When capturing images using a camera, the user is captured from at least one direction, for example, front, back, left, or right. The lying position may be any of a supine position, a lateral position, or a prone position. In the supine or lateral position, the user's posture is close to that of a standing position by lying down so that the angle between the feet and shins is approximately 90 degrees. When the user is captured by the camera in such a posture, imaging data similar to that of the standing position can be acquired.

[0035] Before or after capturing an image, the user operates the operation unit 3b to input body part information indicating the body part captured, into the terminal device 3. For example, "whole body," "upper body," "buttocks," etc. are input. The input body part information is linked to the captured image data, transmitted to the data processing device 2 together with the captured image data, and stored in the storage unit 2c.

[0036] The method of inputting the part information may utilize the stored data described below. For example, the distance for each part may be calculated based on each stored data, and the part may be input based on the calculated distance and the imaging data of the entire body. For example, if the distance from the top of the head to the base of the neck is defined as the length of the "head", the proportion of the "head" distance to the total height is calculated for each stored data, and the average value of each calculated proportion is calculated. The average value of the ratios is applied to the distance from the head. The portion of the imaging data corresponding to the distance obtained by applying the ratio is stored as imaging data for the "head." The same applies to the "upper body." For the "buttocks," for example, for each piece of accumulated data, the ratio of the distance from the top of the head to the top of the buttocks to the total height is calculated, and the average value (first average value) of each calculated ratio is calculated. Also, for each piece of accumulated data, the ratio of the distance from the toes to the total height is calculated, and the average value (second average value) of each calculated ratio is calculated. For imaging data capturing the entire body, the first average value is applied to the distance from the head. Also, for imaging data capturing the entire body, the second average value is applied to the distance from the toes. The distance obtained by applying the first average value and the distance obtained by applying the second average value are subtracted from the total height. The portion of the imaging data corresponding to the distance obtained by the subtraction is stored as imaging data for the "buttocks." Furthermore, each body part may be estimated and stored in accordance with body type data standards established for each race and country, such as JISL0111, ISO3635, and ISO7250.

[0037] Before or after capturing an image, the user operates the operation unit 3b to input biological sex, age, height, weight, and BMI into the terminal device 3. BMI corresponds to information indicating body type. The input sex, age, height, weight, and BMI are linked to the captured image data, transmitted together with the captured image data to the data processing device 2, and stored in the memory unit 2c. Alternatively, any two of height, weight, and BMI may be input into the terminal device 3, and the control unit 2a may calculate the remaining one from the two input height, weight, and BMI, and store it in the memory unit 2c.

[0038] Before or after capturing an image, the user operates the operation unit 3b to input chair type information according to the intended use into the terminal device 3. The chair type information may be, for example, a first type indicating a chair for work, a second type indicating a chair for light work, a third type indicating a chair for light work and light rest, a fourth type indicating a chair for light rest, a fifth type indicating a chair for rest, a sixth type indicating a chair for deep rest, or a seventh type indicating a wheelchair. The input chair type information is transmitted to the data processing device 2 and stored in the memory unit 2c.

[0039] The memory unit 2c stores a plurality of different data (accumulated data) that indicate the overall body surface shape of the human body in a standing position, and a program (program product) that executes processes such as generating sitting posture data, calculating chair design information, and extracting chair product information. Gender, age, height, weight, and BMI are linked to each piece of accumulated data and stored in the memory unit 2c. Various thresholds are stored in the memory unit 2c. The control unit 2a reads the program into RAM 2b and executes information processing such as generating sitting posture data, calculating chair design information, and extracting chair product information.

[0040] The search device 4 stores product information about chairs. The product information about chairs includes, for example, seat height, seat depth, seat width, backrest height, backrest width, armrest height, head support height, seat shape, backrest shape, chair serial number, chair image, and number of chairs in stock. The depth corresponds to the front-to-back dimension, and the width corresponds to the left-to-right dimension. In response to a request from the data processing device 2, the search device 4 searches for product information and transmits it to the data processing device 2. The data processing device 2 transmits the product information to the terminal device 3, and the terminal device 3 displays the product information on the display unit 3a.

[0041] The process of generating sitting posture data will now be described. Fig. 3 is an explanatory diagram for explaining the calculation of the similarity between the captured image data and a plurality of stored data. In Fig. 3, the hatched portion indicates the upper body portion of the stored data, and indicates the portion corresponding to the captured image data.

[0042] For example, as shown in FIG. 3, when the control unit 2a acquires imaging data of the upper body of a human body from the imaging unit 3c, the control unit 2a refers to the part information ("upper body" in this embodiment) linked to the imaging data. Note that the upper body is just an example, and the torso, lower body, buttocks, whole body, etc. may be imaged. Alternatively, captured image data may be used. The upper body portion in each of the plurality of stored data is compared with the image data to calculate the similarity. Examples of similarity include the degree of match between the contour lines of the front or left and right sides of the upper body, or the degree of match between the projected areas of the front or left and right sides of the upper body. The control unit 2a selects one or more stored data with a similarity of 80% or more, preferably 90% or more, and more preferably 95% or more. If there are multiple selected stored data, the stored data with the highest similarity is further selected. For example, as shown in FIG. 3, the control unit 2a further selects one stored data 101 with the highest similarity from the extracted three stored data 101 to 103.

[0043] The weight, height, BMI, and / or age linked to the accumulated data may be compared with the weight, height, BMI, and / or age linked to the imaging data, and the similarity may be corrected so that the smaller the difference in weight, height, BMI, and / or age, the higher the similarity. Alternatively, the BMI may be calculated from the weight and height linked to the accumulated data, and the similarity may be corrected so that the smaller the difference between the BMI calculated from the weight and height of the imaging data and the BMI calculated from the weight and height of the accumulated data, the higher the similarity. The similarity may also be corrected so that the similarity is higher when the gender linked to the accumulated data matches the gender linked to the imaging data.

[0044] 4 is an explanatory diagram illustrating information included in the sitting posture data. The sitting posture data includes the vertical dimension (seat height) Da between the lower surface of the thigh (seat) and the top of the head of the human body in a sitting posture, the vertical dimension (lower thigh height) Db between the sole of the foot and the lower surface of the thigh, the horizontal dimension Dc of the buttocks, the horizontal dimension Dd of the back, the depth dimension De between the knee and the back of the waist (or buttocks), and the vertical dimension Df from the sole of the foot to the elbow.

[0045] The user operates the terminal device 3 to capture an image of at least a part of their body using the imaging unit 3c, inputs information such as body part information, gender, age, height, weight, and BMI, and sends an instruction to start information processing to the data processing device 2.

[0046] Fig. 5 is a flowchart illustrating information processing by the data processing device 2. As shown in Fig. 5, the control unit 2a of the data processing device 2 determines whether an instruction to start information processing has been input from the terminal device 3 (S1). If the instruction to start has not been input (S1: NO), the process returns to step S1. If the instruction to start has been input (S1: YES), the control unit 2a acquires imaging data from the terminal device 3 (S2), acquires information such as body part information, sex, age, height, weight, and BMI (S3), and acquires chair type information (S4). The control unit 2a selects one of the stored data from the memory unit 2c (S5).

[0047] The control unit 2a extracts the body surface shape of the stored data corresponding to the body surface shape of the part indicated by the imaging data (S6), calculates the similarity between the extracted body surface shape of the stored data and the body surface shape of the imaging data, and determines whether the similarity is equal to or greater than a threshold (S7). As described above, the similarity may be corrected based on weight, height, or BMI. If the similarity is equal to or greater than the threshold (S7: YES), the control unit 2a stores the selected stored data in the storage unit 2c (S8) and determines whether all of the stored data and the imaging data have been compared (S9). If the similarity is not equal to or greater than the threshold (S7: NO) in step S7, i.e., if the similarity is less than the threshold, the control unit 2a proceeds to step S9.

[0048] In step S8, if not all of the stored data have been compared with the imaging data (S9: NO), the control unit 2a returns the process to step S5 and selects the next stored data (S5). The control unit 2a sequentially selects multiple stored data. In step S9, if all of the stored data have been compared with the imaging data (S9: YES), the control unit 2a selects the stored data with the highest similarity from the stored data whose similarity is equal to or greater than the threshold (S10).

[0049] The control unit 2a generates sitting posture data based on the selected stored data (S11, see FIG. 4). The stored data is image data relating to at least a portion of the body surface shape in a standing position. For example, the control unit 2a converts the position information of the stored data into position information of the sitting posture, and also corrects the length of each part indicated by the stored data to generate sitting posture data. For example, the control unit 2a converts the knee position in the stored data into a position rotated approximately 90 degrees forward around the waist. The control unit 2a also converts the lower leg and foot into a position rotated approximately 90 degrees downward around the knee. The control unit 2a also converts the hand and forearm into a position rotated approximately 90 degrees forward around the elbow. The control unit 2a also generates the seat height Da, the lower leg height Db, the horizontal dimension Dc of the buttocks, the horizontal dimension Dd of the back, the depth dimension De from the knee to the back of the waist (or buttocks), and the vertical dimension Df from the sole to the elbow.

[0050] Considering that the width of the buttocks in a sitting position increases slightly, the control unit 2a may set the width Dc of the buttocks in the sitting position to a value slightly larger than the width of the buttocks in the accumulated data, for example, a value obtained by multiplying the width of the buttocks in the accumulated data by approximately 1.1. Alternatively, the depth De may be defined as the length of the thigh plus the front-to-back width of the waist or buttocks, and the length of the thigh in the accumulated data may be multiplied by approximately 1.2 to set the depth De.

[0051] If the height of a human body in a standing position is H, the seat height Da is approximately (6 / 11)H, and the lower leg height Db is approximately (1 / 4)H. Therefore, the control unit 2a may calculate the seat height Da based on the height H and the ratio 6 / 11. For example, the control unit 2a may calculate the seat height Da by multiplying the height H by a ratio between 6.2 / 11 and 5.8 / 11. The control unit 2a may calculate the seat height Da based on the height H and the ratio 1 / 4. For example, the control unit 2a may calculate the seat height Da by multiplying the height H by a ratio between 1.1 / 4 and 0.9 / 4. Similarly, the horizontal dimension of the buttocks Dc, the horizontal dimension of the back Dd, the depth dimension De from the knees to the back of the hips (or buttocks), and the vertical dimension Df from the soles to the elbows may also be calculated by multiplying a reference value by a ratio. Note that the sitting posture data may be calculated by division, addition, or subtraction, rather than by multiplication.

[0052] The control unit 2a calculates design information based on the generated sitting posture data and the acquired chair type information (see step S4) (S12).

[0053] FIG. 6 is an explanatory diagram illustrating design information. The design information includes the dimensions and curvature of each part of the chair that corresponds to the shape of the user's body surface. In the following description, "height" refers to the upward distance from the soles of the user's feet or the floor / ground on which the chair is placed. The design information includes, for example, the chair's seat height K1, seat depth K2, seat width K3, backrest vertical dimension K4, backrest width K5, armrest height K6, head support vertical dimension K7, backrest curvature R1, curvature R2 of the connecting portion of the seat and backrest, angle θ1 between the horizontal plane and the seat, and angle θ2 between the seat and backrest.

[0054] For example, the seat height K1 of a chair is calculated by the lower leg height Db in a seated position multiplied by coefficients A1 to A7. The seat depth K2 is calculated by the depth dimension De between the knees and the back of the waist (or buttocks) multiplied by coefficients B1 to B7. The seat width K3 is calculated by the width dimension Dc of the buttocks in a seated position multiplied by coefficients C1 to C7. The backrest vertical dimension K4 is calculated by the seat height Da multiplied by coefficients D1 to D7. The backrest horizontal dimension K5 is calculated by the width dimension Dd of the back multiplied by coefficients E1 to E7. The armrest height K6 is calculated by the vertical dimension Df from the sole of the foot to the elbow multiplied by coefficients F1 to F7. The coefficients A1 to A7 are coefficients corresponding to the first to seventh types of type information, respectively, and are stored in advance in the memory unit 2c. Similarly, the coefficients B1 to B7, C1 to C7, D1 to D7, E1 to E7, and F1 to F7 correspond to the first to seventh types of type information, respectively, and are stored in advance in the storage unit 2c.

[0055] The vertical dimension K7 of the head support is calculated by the seat height Da minus the vertical dimension K4 of the backrest. The curvature R1 of the backrest is calculated by the curvature R1 corresponding to each of the first to seventh types of type information. The curvature R2 of the connecting portion of the seat and backrest includes curvatures R2a to R2g corresponding to the first to seventh types of type information, and is pre-stored in the storage unit 2c. The angle θ1 between the horizontal plane and the seat includes angles θ1a to θ1g corresponding to the first to seventh types of type information, and is pre-stored in the storage unit 2c. The angles θ1a to θ1g are, for example, in the range of 0 to 30 degrees, and the angles increase in ascending order from the first type to the sixth type. The angle θ1g of the seventh type (wheelchair) may be an angle different from θ1a to θ1f, may be the same as any of θ1a to θ1f, or may be selected according to the user's preference. The angle θ2 between the seat and backrest includes angles θ2a to θ2g corresponding to the first to seventh types of type information, and is pre-stored in the storage unit 2c. The angles θ2a to θ2g are, for example, in the range of 90 to 130 degrees, and the angles increase in ascending order from Type 1 to Type 6. The angle θ2g of Type 7 (wheelchair) may be an angle different from θ2a to θ2f, may be the same as any of θ2a to θ2f, or may be selected according to the user's preference.

[0056] The control unit 2a calculates the chair seat height K1, seat depth K2, seat width K3, backrest vertical dimension K4, backrest width K5, armrest height K6, and head support vertical dimension K7 corresponding to the acquired type information types 1 to 7. The control unit 2a may also calculate the backrest curvature R1, the curvature R2 of the connecting portion of the seat and backrest, the angle θ1 between the horizontal plane and the seat, and the angle θ2 between the seat and backrest corresponding to the first to seventh types based on the sitting posture data.

[0057] The control unit 2a uses a search device 4 that stores information on multiple ready-made chairs to extract product information that is close to the calculated design information, i.e., information on chairs that have design information that is close to the calculated design information, from the information on multiple ready-made chairs (S13). For example, when the control unit 2a calculates the difference between each piece of information constituting the calculated design information (chair seat height K1, seat depth K2, seat width K3, backrest vertical dimension K4, backrest width K5, armrest height K6, head support vertical dimension K7, backrest curvature R1, curvature R2 of the connecting portion of the seat and backrest, angle θ1 between the horizontal plane and the seat, angle θ2 between the seat and backrest, etc.) and each piece of information constituting the design information of a ready-made chair, the control unit 2a checks whether the sum of the absolute values ​​of each difference is equal to or less than a threshold value and whether the absolute value of each difference is within 20% of each piece of information constituting the calculated design information (i.e., the error for each piece of information with respect to the calculated design information is within 20%), i.e., transmits the search conditions to the search device 4. The search device 4 searches for product information that matches the search conditions and transmits it to the data processing device 2. The control unit 2a sorts the received product information in descending order based on the total, and extracts the first to third ranked product information.

[0058] The control unit 2a transmits the extracted first to third product information to the terminal device 3 and displays it on the display unit 3a (S14). The product information transmitted to the terminal device 3 also includes product images, product numbers, product names, etc. The control unit 2a determines whether or not it has accepted that the user has operated the operation unit 3b to select one of the first to third product information (S15). If the selection of product information has not been accepted (S15: NO), the control unit 2a returns the process to step S15. If the selection of product information has been accepted (S15: YES), the control unit 2a determines whether or not it has accepted that the user has operated the operation unit 3b to select accessories such as a cover and cushion to be provided for the product (chair) related to the selected product information, or the material of the product itself (step S16). If the selection of accessories or the material of the product itself has not been accepted (S16: NO), the control unit 2a returns the process to step S16. When it is accepted that an accessory or the material of the product itself has been selected (S16: YES), the control unit 2a determines the selected product information and material and the selected accessory as the product desired by the user, transmits information about the desired product to the terminal device 3, causes the display unit 3a to display the information about the desired product (S17), and ends the process.

[0059] The data processing device 2 may execute a purchase process when it receives a purchase decision command from the terminal device 3. For example, the control unit 2a accesses inventory data, and if the desired product is in stock, executes a delivery procedure process, and if it is out of stock, sends a notice to the terminal device 3 that the product is waiting for production.

[0060] The sitting posture data processing system 1 is not limited to a configuration in which the data processing device 2, the terminal device 3, and the search device 4 are capable of communicating with each other. For example, any two or all of the data processing device 2, the terminal device 3, and the search device 4 may constitute a single device.

[0061] In selecting the stored data in step S10, multiple stored data may be selected. For example, the first stored data with the highest similarity, the second stored data with the next highest similarity after the first stored data, and the third stored data with the next highest similarity after the second stored data may be selected, and sitting posture data may be generated for each of the first to third stored data, design information may be calculated, and product information may be extracted and displayed. Alternatively, the average value or root mean square of the dimensions of each part of the sitting posture data generated for each of the first to third stored data may be determined as the dimension of each part of the sitting posture data. Alternatively, the average value or root mean square of the design information calculated for each of the first to third stored data may be determined as the design information.

[0062] In step S16, the control unit 2a may apply the selected accessories, such as a cover and cushion, or the selected material of the product itself, to the product (chair) related to the selected product information, and cause the terminal device 3 to display an image showing the product after application. The user can check images showing multiple products with different accessories or materials applied and select one of the products to which the accessories or materials have been applied. In other words, the user can check the state in which the accessories or materials have been applied to the product and select the accessory or material. Alternatively, the control unit 2a may cause the terminal device 3 to display images showing the accessories and materials next to the product image, without displaying an image of the accessories and materials applied to the product.

[0063] In the sitting posture data processing system 1, data processing device 2, and computer program according to the first embodiment, sitting posture data is generated based on imaging data relating to the body surface shape of at least a part of the human body. Chair information is displayed based on the generated sitting posture data. A user can obtain information about a chair that suits their body simply by imaging their own body in a standing, sitting, or lying position.

[0064] In addition, the imaging data can be compared with multiple different stored data that show the overall body surface shape of the human body, at least one stored data with a high degree of similarity can be selected, and data showing the sitting posture can be generated based on the selected stored data.

[0065] When imaging his or her own body, the user can select either a standing or sitting position, and stored data having similar body information to that of the user is selected.

[0066] For example, based on an operation by a user, one piece of product information is selected from the product information of at least one chair. The selected product information is checked against, for example, inventory data of chairs to confirm whether the chair is in stock.

[0067] (Embodiment 2) The present invention will be described below with reference to the drawings showing a chair manufacturing apparatus according to embodiment 2. Among the components according to embodiment 2, the same components as those in embodiment 1 are given the same reference numerals, and detailed description thereof will be omitted.

[0068] FIG. 7 is a block diagram of a chair manufacturing device. In the second embodiment, the device includes a sitting posture data processing system 1 and a manufacturing device 5. The manufacturing device 5 is a machine tool, a 3D printer, or the like. In the above-mentioned step S12, when the design information is calculated, the data processing device 2 transmits the image of the chair related to the design information and the design information to the terminal device 3. The terminal device 3 displays the image of the chair and the design information on the display unit 3a.

[0069] When a user operates the operation unit 3b and inputs an order command for a chair related to the design information into the terminal device 3, the data processing device 2 transmits the order command and the design information to the manufacturing device 5. The operator of the manufacturing device 5 manufactures the chair using the manufacturing device 5 based on the design information. Note that the manufacturing device 5 may automatically manufacture the chair without relying on the operation of the operator.

[0070] In the chair manufacturing apparatus and chair manufacturing method according to the second embodiment, the manufacturing apparatus 5 manufactures a chair that fits the user's body based on the design information. That is, a custom-made chair that fits the user's body surface shape is manufactured.

[0071] (Embodiment 3) The present invention will be described below with reference to the drawings showing a bedding manufacturing apparatus according to a third embodiment. Among the components of the third embodiment, components similar to those of the first or second embodiment are designated by the same reference numerals, and detailed description thereof will be omitted. The memory unit 2c of the data processing device 2 stores a learning model 100. FIG. 8 is a schematic diagram showing an example of the learning model 100. The learning model 100 is a learning model intended for use as a program module that is part of artificial intelligence software, and can use a multi-layer neural network (deep learning). For example, a convolutional neural network (CNN) can be used. Note that other machine learning methods may also be used. The control unit 2a loads the learning model 100 into RAM 2b, and operates in accordance with instructions from the learning model 100 to perform calculations on the input data input to the input layer of the learning model 100, i.e., the image data and human body information such as gender, height, weight, and / or BMI, and output product information from the output layer.

[0072] The control unit 2a uses the training data to generate in advance a learning model 100 that outputs product information when imaging data and human body information are input. Specifically, the control unit 2a inputs the training data to the input layer, performs calculation processing in the intermediate layer, and acquires the product information from the output layer.

[0073] The control unit 2a compares the product information output from the output layer with the product information labeled for the imaging data and human body information in the training data, i.e., the correct value, and optimizes the parameters used in the calculation process in the intermediate layer so that the output value from the output layer approaches the correct value. The parameters include, for example, the weights (combining coefficients) and activation function coefficients described above. There are no particular limitations on the method for optimizing the parameters, and the control unit 2a may, for example, optimize various parameters using the backpropagation method. The control unit 2a stores the generated learning model 100 in the memory unit 2c and completes the series of processes for the learning model 100. The control unit 2a may also re-learn the learning model 100.

[0074] The control unit 2a inputs the imaging data and human body information into the trained learning model 100, and acquires product information and its probability. The control unit 2a transmits, for example, three pieces of product information to the terminal device 3. For example, it transmits product information 1 with the highest probability, product information 2 with the second highest probability, and product information 3 with the third highest probability, and causes the display unit 3a to display them. Thereafter, the control unit 2a performs the same processes as steps S15 to S17 described above.

[0075] The product information labeled with the imaging data and human body information in the training data may be only a part of the product information. For example, only the serial number of a chair may be labeled. In this case, the control unit 2a transmits, for example, the serial numbers of three pieces of product information with high probability to the search device 4. The search device 4 searches for product information related to the received serial numbers and transmits it to the data processing device 2. The data processing device 2 transmits the three pieces of product information received from the search device 4 to the terminal device 3. Deep learning is an example of machine learning, and other machine learning techniques, such as decision tree learning, clustering, or Bayesian learning, may be used instead of deep learning.

[0076] It should be noted that a computer program can be deployed to be executed on a single computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communications network.

[0077] The embodiments disclosed herein are illustrative in all respects and should not be considered limiting. The scope of the present invention is intended to include all modifications within the scope of the claims and the scope equivalent to the claims. The features described in each embodiment can be mutually combined. Furthermore, independent claims and dependent claims described in the claims can be mutually combined in any and all combinations, regardless of the reference format. Furthermore, although the claims use a format in which a claim references two or more other claims (multiple claim format), this is not limiting. A multiple claim (multi-multi claim) that references at least one other multiple claim may also be used. [Explanation of symbols]

[0078] 1. Sitting posture data processing system 2. Data Processing Device 2a Control section 2b RAM 2c storage section 2d Communication Department 3 Terminal 3a Display section 3b Operation section 3c Imaging unit 3d communication department 4 Search Device 5 Manufacturing equipment

Claims

1. an imaging data acquisition unit that acquires imaging data relating to a body surface shape of at least a part of a human body; a generation unit that generates sitting posture data indicating a sitting posture of a human body based on the imaging data acquired by the imaging data acquisition unit; an output unit that outputs information about the chair to a display unit based on the sitting posture data generated by the generation unit; A sitting posture data processing device comprising:

2. a similarity calculation unit that calculates a similarity between the imaging data acquired by the imaging data acquisition unit and each of a plurality of different accumulated data that are stored in advance and indicate the entire body surface shape of the human body; a selection unit that selects at least one of the stored data items according to the similarity calculated by the similarity calculation unit; Equipped with The generating unit generates sitting posture data indicating a sitting posture of a human body based on the selected stored data. The sitting posture data processing device according to claim 1 .

3. The imaging data is data relating to the shape of at least a part of the body surface of a human body in a standing or sitting position. The sitting posture data processing device according to claim 1 or 2.

4. a human body information acquisition unit that acquires human body information indicating sex, age, height, weight, or body type; The similarity calculation unit calculates the similarity based on the human body information acquired by the human body information acquisition unit. The sitting posture data processing device according to claim 2 .

5. a type acquisition unit that acquires a type of chair according to a purpose of use; a design information calculation unit that calculates design information including dimensions of the chair based on the sitting posture data generated by the generation unit and the type of chair acquired by the type acquisition unit; Equipped with The output unit outputs product information of at least one chair to the display unit based on the design information calculated by the design information calculation unit. The sitting posture data processing device according to claim 1 or 2.

6. a receiving unit that receives a selection of one of the pieces of product information from the product information output on the display unit; The sitting posture data processing device according to claim 5 .

7. an imaging unit that images a body surface shape of at least a part of a human body; an imaging data acquisition unit that acquires imaging data from the imaging unit; a generation unit that generates sitting posture data indicating a sitting posture of a human body based on the imaging data acquired by the imaging data acquisition unit; an output unit that outputs information about a chair based on the sitting posture data generated by the generation unit; a display unit that displays the information about the chair output from the output unit; A sitting posture data processing system comprising:

8. an imaging data acquisition unit that acquires imaging data relating to a body surface shape of at least a part of a human body; A sitting posture of a human body is indicated based on the imaging data acquired by the imaging data acquisition unit. a generation unit for generating sitting posture data; a type acquisition unit that acquires a type of chair according to a purpose of use; a design information calculation unit that calculates design information including dimensions of the chair based on the sitting posture data generated by the generation unit and the type of chair acquired by the type acquisition unit; a manufacturing unit that manufactures chairs based on the design information calculated by the design information calculation unit; A chair manufacturing apparatus comprising:

9. acquiring imaging data relating to a body surface shape of at least a portion of a human body; generating sitting posture data indicating a sitting posture of the human body based on the acquired imaging data; Obtain the type of chair according to the purpose of use, calculating design information including dimensions of the chair based on the generated sitting posture data and the acquired type of chair; Manufacture a chair based on the calculated design information. How to make a chair.

10. acquiring imaging data relating to a body surface shape of at least a portion of a human body; generating sitting posture data indicating a sitting posture of the human body based on the acquired imaging data; The information about the chair corresponding to the sitting posture data is output to a display unit. A computer program that causes a computer to perform a process.

11. an imaging data acquisition unit that acquires imaging data relating to a body surface shape of at least a part of a human body; a human body information acquisition unit that acquires human body information indicating gender, height, weight, or body type; an information acquisition unit that acquires the product information of a chair by inputting the imaging data acquired by the imaging data acquisition unit and the human body information acquired by the human body information acquisition unit into a learning model that uses product information of a chair as training data and outputs product information of a chair when imaging data and human body information are input; an output unit that outputs the product information of the chair acquired by the information acquisition unit to a display unit; A chair data processing device comprising:

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