Abstract: In a shoe fit evaluation system, a dimensional difference calculator calculates a part dimensional difference, which is a difference between a measurement value of a foot part dimension and a last part dimension corresponding to the foot part, by performing a certain adjustment for the part. An evaluation processor calculates a last matching rate based on the part dimensional difference. An outputter outputs information regarding the last matching rate. The dimensional difference calculator calculates the part dimensional difference by performing, as the certain adjustment, subtraction of an allowance for specific stretch properties of each shoe part.

Abstract: An information notification device includes a longitudinal-data storage unit that accumulates, for a plurality of samples, longitudinal data indicating a temporal change in foot size of one sample, a user-data storage unit that stores user data containing a gender, an age, and a past foot size of a prediction target person, a foot-size prediction unit that predicts, based on a current foot size of the prediction target person and the longitudinal data, a change in foot size of the prediction target person in a period from a current point in time to a future point in time, and a notification processing unit that displays, on a display unit, the prediction of the change in foot size of the prediction target person in the period from the current point in time to the future point in time.

Abstract: A sock liner designing apparatus, a sock liner designing method and a recording medium for a recording program are provided that are used to design sock liners that enable functions of footwear desired by a user to be attained when the user wears the footwear. A sock liner designing apparatus includes: an input circuitry that receives an input of measured foot data; a processor that calculates design data of a sock liner based on the foot data received through the input circuitry; and an output circuitry that outputs the design data calculated by the processor. The processor adjusts the design data based on a difference between received footwear functions and footwear data.

Abstract: A sockliner includes: a base layer portion formed of a three-dimensional mesh structure body; and an upper layer portion formed of a sheet-like structure body that covers an upper surface of the base layer portion. The upper layer portion includes a through-hole group including a plurality of holes, and each of the holes is located inward from a peripheral edge of the upper layer portion without reaching the peripheral edge. In a case where a surrounding region is defined as a region between the peripheral edge and a position offset by 4.0 mm inward from the peripheral edge, the through-hole group includes an outermost hole group including a plurality of holes located closest to the peripheral edge so as to overlap with the surrounding region and to align along the peripheral edge.

Abstract: A shoe purchase recommendation device 10A includes a user information acquisition unit that acquires user information including a first foot size that is a foot size of a user, a foot-size prediction unit that predicts, based on the first foot size of the user, a second foot size that is a foot size of the user at a future point of time, a growth-end determination unit that determines, based on the second foot size, whether foot growth of the user has ended at the future point of time, a product information storage unit that stores child product information and adult product information, a product information selection unit that selects, based on a result determined by the growth-end determination unit, product information regarding shoes from one of the child product information and the adult product information, and a display processing unit that displays the product information regarding shoes selected by the product information selection unit on a display unit.

Abstract: A prediction device includes: a communication device that acquires measurement subject data including measurement data of a shape of a foot of a measurement subject person in a loaded state; a storage that stores first sample data in the loaded state and second sample data in an unloaded state, the first sample data and the second sample data being calculated from measurement data of foot shapes of a plurality of samples, the samples being identical both in the loaded state and the unloaded state; and a processor that predicts the shape of the foot of the measurement subject person in the unloaded state. The processor calculates a difference between the measurement subject data and the first sample data, and predicts the shape of the foot of the measurement subject person in the unloaded state based on the difference and the second sample data.

Abstract: A prediction device includes: a communication device that acquires measurement subject data including measurement data of a shape of a foot of a measurement subject person in a loaded state; a storage that stores first sample data in the loaded state and second sample data in an unloaded state, the first sample data and the second sample data being calculated from measurement data of foot shapes of a plurality of samples, the samples being identical both in the loaded state and the unloaded state; and a processor that predicts the shape of the foot of the measurement subject person in the unloaded state. The processor calculates a difference between the measurement subject data and the first sample data, and predicts the shape of the foot of the measurement subject person in the unloaded state based on the difference and the second sample data.

Abstract: In a markerless foot size estimation device 100, a shape data input unit 10 acquires three-dimensional shape data of a foot of a subject and stores the three-dimensional shape data in a shape data storage unit 20. A characteristic extraction unit 30 extracts foot shape characteristics from the three-dimensional shape data of a subject's foot stored in the shape data storage unit 20, and stores the foot shape characteristics in a shape characteristic storage unit 40. A machine learning unit 50 uses, as teacher data, foot shape characteristics and arch height stored in the shape characteristic storage unit 40 to create, through machine learning, an estimation model used to estimate arch height based on foot shape characteristics, and stores the estimation model in an estimation model storage unit 60. An estimation output unit 70 uses the estimation model stored in the estimation model storage unit 60 to estimate arch height based on extracted shape characteristics and outputs the arch height.

Abstract: In a markerless foot size estimation device 100, a shape data input unit 10 acquires three-dimensional shape data of a foot of a subject and stores the three-dimensional shape data in a shape data storage unit 20. A characteristic extraction unit 30 extracts foot shape characteristics from the three-dimensional shape data of a subject's foot stored in the shape data storage unit 20, and stores the foot shape characteristics in a shape characteristic storage unit 40. A machine learning unit 50 uses, as teacher data, foot shape characteristics and arch height stored in the shape characteristic storage unit 40 to create, through machine learning, an estimation model used to estimate arch height based on foot shape characteristics, and stores the estimation model in an estimation model storage unit 60. An estimation output unit 70 uses the estimation model stored in the estimation model storage unit 60 to estimate arch height based on extracted shape characteristics and outputs the arch height.

Abstract: A shoe shape selection method selects an appropriate shoe shape from a plurality of kinds of shoe shapes prepared beforehand, based on a plurality of items of data on a customer. The plurality of data items include the foot length of the customer, the foot girth of the customer and the difference between the lengths of the first and second toes of the customer.

Abstract: In a foot inclination angle measuring method of the present application, the shape of a foot 10 is measured in three dimensions. And, based on three-dimensional data on the measured shape of the foot 10, a two-dimensional cross section 30 of the foot 10 orienting in a front-rear direction, which includes a cross section of a heel of the foot 10, is obtained. Then, a central line C1 of the two-dimensional cross section 30 in a right-left direction is obtained and the angle of inward/outward inclination of the foot 10 is obtained from the angle of inclination (a) of the central line C1.

Abstract: A shoe shape selection method selects an appropriate shoe shape from a plurality of kinds of shoe shapes prepared beforehand, based on a plurality of items of data on a customer. The plurality of data items include the foot length of the customer, the foot girth of the customer and the difference between the lengths of the first and second toes of the customer.

Abstract: In a foot inclination angle measuring method of the present application, the shape of a foot 10 is measured in three dimensions. And, based on three-dimensional data on the measured shape of the foot 10, a two-dimensional cross section 30 of the foot 10 orienting in a front-rear direction, which includes a cross section of a heel of the foot 10, is obtained. Then, a central line C1 of the two-dimensional cross section 30 in a right-left direction is obtained and the angle of inward/outward inclination of the foot 10 is obtained from the angle of inclination (a) of the central line C1.