Asics Corporation

Kazunari Takeichi

Norihiko Taniguchi

Takehiro Tagawa

Masaru Ichikawa

Ryota Shinayama

Hiroyuki Kusumi

Kana Kagami

In a markerless foot size estimation device, a shape data input unitacquires three-dimensional shape data of a foot of a subject and stores the three-dimensional shape data in a shape data storage unit. A characteristic extraction unitextracts foot shape characteristics from the three-dimensional shape data of a subject's foot stored in the shape data storage unit, and stores the foot shape characteristics in a shape characteristic storage unit. A machine learning unituses, as teacher data, foot shape characteristics and arch height stored in the shape characteristic storage unitto 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. An estimation output unituses the estimation model stored in the estimation model storage unitto estimate arch height based on extracted shape characteristics and outputs the arch height.

Markerless foot size estimation device, markerless foot size estimation method, and markerless foot size estimation program

A measuring board having a simple structure is to be provided. A measuring board includes a main body having a foldable structure, and the main body includes a placement part on which a foot is placed and that includes a measurement marker, a wall part provided adjacent to the placement part and configured to position a heel during measurement, and supporting structures and that support the wall part. With such a configuration, a measuring board having a simple structure can be provided.

Measuring board and foot shape data creating system

A motion state evaluation system is provided with a motion analyzer obtains a value representing a motion state of the subject based on a ratio, to a reference length, of a distance between predetermined joints estimated on an image; a reference storage stores a height of a subject as the reference length; a motion analyzer obtains, as a value for use in evaluation of motion of the subject, the value representing the motion state of the subject from a feature point distance on the image of a plurality of anatomical feature points based on a ratio, to the height, of a distance on the image that is determined from the plurality of anatomical feature points and corresponds to the height of the subject; and an evaluation processor evaluates the motion of the subject based on the value representing the motion state.

Motion state evaluation system, motion state evaluation device, motion state evaluation server, motion state evaluation method, and motion state evaluation program

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Kobe, Japan

Kazunari Takeichi