Abstract: Disclosed is a platform for generating and delivering 3-D printed wearables. The platform includes scanning, image processing, machine learning, computer vision, and user input to generate a printed wearable. Scanning occurs in a number of ways across a number of devices. The variability of scanning generates a number of scanning output types. Outputs from the scanning process are normalized into a single type during image processing. The computer vision and machine learning portions of the platform use the normalized body scan to develop models that may be used by a 3D printer to generate a wearable customized to the user. The platform further provides opportunities for the user to check the work of the scanning, image processing, computer vision, and machine learning. The user input enables the platform to improve and inform the machine learning aspects.

Abstract: A method for manufacturing a sandal, wherein various aspects of said sandal may be customized for a wearer's feet. The aspects can involve one or more of: the toe thong location, the position of the foot strap, and the arch support profile and arch support position. For a particular wearer, the optimal locations/settings of one or more of the foregoing aspects may be determined by applying a computer algorithm, which takes into account the foot data of the wearer, which foot data may be obtained from image/video capture technology. The method then assembles a sandal having the optimal locations/settings, such that the foot strap position, the arch support profile and/or the arch support position, as the case may be, are customized for the wearer. Also disclosed herein is a sandal having a foot strap position and/or an arch support profile and arch support position that is customized for the wearer, and made in accordance with the above-described methods.

Abstract: Disclosed herein is a technique to efficiently pack a print volume of 3D printers having print jobs with a large number of objects. The technique positions unique objects that adhere to a similar structural pattern more closely when the degree of variation between the objects is small. Thus, while each object is unique, a greater extent of similarity between the objects causes a given group of objects to be positioned more closely to one another in the print area of the 3D printer.

Abstract: The disclosed technique relates to an insert for footwear and to a composite orthotic insole comprising said insert, wherein the insert is embedded with a plurality of force (or pressure) sensors, and may be used to provide feedback on important information regarding the wearer's gait biomechanics. The layer of sensors may be used to assist in monitoring the wearer's health via foot pressure tracking. The insole can use a relative large number of sensors, which together provide broad coverage of the human foot impact area.

Abstract: A method for manufacturing a sandal, wherein the toe thong location of said sandal is customised for a wearer. For a particular wearer, the optimal location of the toe thong of the sandal may be determined by applying a computer algorithm, which takes into account foot data of the wearer, which foot data may be obtained from image/video capture technology. The method makes use of a custom toe thong insert, which is embedded within the sole of the sandal. The custom toe thong insert is configured to receive and securely engage with a fastener attached to the toe thong and foot strap, such that the toe thong will be positioned at or proximate to the optimal location for the particular wearer. Also disclosed herein is a sandal with a customised toe thong location that is made in accordance with the above-described method.

Abstract: Disclosed is a platform for generating and delivering 3-D printed wearables. The platform includes scanning, image processing, machine learning, computer vision, and user input to generate a printed wearable. Scanning occurs in a number of ways across a number of devices. The variability of scanning generates a number of scanning output types. Outputs from the scanning process are normalized into a single type during image processing. The computer vision and machine learning portions of the platform use the normalized body scan to develop models that may be used by a 3D printer to generate a wearable customized to the user. The platform further provides opportunities for the user to check the work of the scanning, image processing, computer vision, and machine learning. The user input enables the platform to improve and inform the machine learning aspects.