3D Foot Scan to Custom Shoe Last

Today’s customers not only look at aesthetic beauty but also quality, comfort and fit. New technologies such as digitization and virtual 3D tailoring are providing more options to consumers and designers in designing different styles with the least possible time. Next to the shoe fashion and style, good fit and comfort are the second important determinant in the purchase of footwear. Although there is a need for better fitting, there are no techniques for fit quantification. In traditional shoemaking, the shoe is categorized by the length and width (or girth), hence there is always a mismatch between the complex foot shape and shoe shape. For the industry in order to meet the demand for better footwear, new techniques for fit quantification is required in order to have a direct mapping form foot to shoe-last (a mold for making shoes). In recent years, with the rapid development of computer technology and advanced design and manufacturing technologies such as computer-aided design (CAD) and computer-aided manufacturing (CAM), the manufacturing of customized shoe lasts is becoming possible. Still research is needed to find the best shoe-last. This paper discusses the basic concepts and current methods being followed to convert foot to shoe-last, retrieve the best fitting shoe last based on the 3D foot scan of the customer, and to obtain customized shoe last

Developing a three-dimensional (3D) assessment method for clubfoot-A study protocol

© 2018 Ganesan, Luximon, Al-Jumaily, Yip, Gibbons and Chivers. Background: Congenital talipes equinovarus (CTEV) or clubfoot is a common pediatric congenital foot deformity that occurs 1 in 1,000 live births. Clubfoot is characterized by four types of foot deformities: hindfoot equinus; midfoot cavus; forefoot adductus; and hindfoot varus. A structured assessment method for clubfoot is essential for quantifying the initial severity of clubfoot deformity and recording the progress of clubfoot intervention. Aim: This study aims to develop a three-dimensional (3D) assessment method to evaluate the initial severity of the clubfoot and monitor the structural changes of the clubfoot after each casting intervention. In addition, this study explores the relationship between the thermophysiological changes in the clubfoot at each stage of the casting intervention and in the normal foot. Methods: In this study, a total of 10 clubfoot children who are < 2 years old will be recruited. Also, the data of the unaffected feet of a total of 10 children with unilateral clubfoot will be obtained as a reference for normal feet. A Kinect 3D scanner will be used to collect the 3D images of the clubfoot and normal foot, and an Infrared thermography camera (IRT camera) will be used to collect the thermal images of the clubfoot. Three-dimensional scanning and IR imaging will be performed on the foot once a week before casting. In total, 6-8 scanning sessions will be performed for each child participant. The following parameters will be calculated as outcome measures to predict, monitor, and quantify the severity of the clubfoot: Angles cross section parameters, such as length, width, and the radial distance; distance between selected anatomical landmarks, and skin temperature of the clubfoot and normal foot. The skin temperature will be collected on selected areas (forefoot, mid foot, and hindfoot) to find out the relationship between the thermophysiological changes in the clubfoot at each stage of the casting treatment and in the normal foot. Ethics: The study has been reviewed and approved on 17 August 2016 by the Sydney Children's Hospitals Network Human Research Ethics Committee (SCHN HREC), Sydney, Australia. The Human Research Ethics Committee (HREC) registration number for this study is: HREC/16/SCHN/163

Dynamic Footwear Fit Model Similar to NIOSH Lifting Equation

AbstractImproper footwear design causes injuries and illnesses, and hence it is important to understand not only the foot but also the footwear. In order to reduce injuries and illnesses, the foot and footwear have to match in such a way to avoid high pressure points and friction due to movements. As far as footwear fit is concerned, literature review has indicated that static footwear fit has mostly been studied, even though dynamic pressure, friction, and foot movement beyond the normal range of motion will cause different type of injuries and illnesses when compared to static fit. Therefore, this paper proposes a theoretical model for dynamic fit. The dynamic footwear fit model is developed similar to the NIOSH lifting equation. The dynamic fit is related to static fit and several multipliers related to footwear design, material properties, and time factor. More research is being carried out to set the parameter values of the theoretical model. The importance of this model is useful for quantification of dynamic footwear fit as it is more related to the actual situation. Better footwear fit, both static and dynamic, will generally improve foot health

Foot Modeling and Footwear Development

Institute of Textiles and Clothin

A shoe-last selection system based on fit rating

Footwear performance can be broadly evaluated based on its function, appearance, and fit. In many cases, fit can govern functions and is hence an important property. The shoe-last, a solid 3D mould around which a shoe is made, has relatively complex shape without any straight lines and is normally made of high density polyethylene for footwear production. The most important aspect of footwear customisation is to design a customised and better fitting shoe-last. The traditional method to make customise shoe-last form foot measurements is very tedious, foot print and ball girth is used. Due to a move toward mass-customisation, it is essential to realise design automation and manufacture automation in footwear industry. With the proliferation of e-commerce, it is unnecessary and improbable to ask customers to come to the retail store and try the shoes on. Footwear customisation and purchase through the internet would be greatly enhanced if a speedy and precise computerised fit rating method could be presented. This study present a system to help shoe-last designer to select the best fit shoe last based on a given foot shape. Some novel algorithms and functions were proposed to improve the accuracy of fit rating based on 3D error mapping.; Footwear performance can be broadly evaluated based on its function, appearance, and fit. In many cases, fit can govern functions and is hence an important property. The shoe-last, a solid 3D mould around which a shoe is made, has relatively complex shape without any straight lines and is normally made of high density polyethylene for footwear production. The most important aspect of footwear customisation is to design a customised and better fitting shoe-last. The traditional method to make customise shoe-last form foot measurements is very tedious, foot print and ball girth is used. Due to a move toward mass-customisation, it is essential to realise design automation and manufacture automation in footwear industry. With the proliferation of e-commerce, it is unnecessary and improbable to ask customers to come to the retail store and try the shoes on. Footwear customisation and purchase through the internet would be greatly enhanced if a speedy and precise computerised fit rating method could be presented. This study present a system to help shoe-last designer to select the best fit shoe last based on a given foot shape. Some novel algorithms and functions were proposed to improve the accuracy of fit rating based on 3D error mapping.Institute of Textiles and Clothin

3D foot shape generation from 2D information

Two methods to generate an individual 3D foot shape from 2D information are proposed. A standard foot shape was first generated and then scaled based on known 2D information. In the first method, the foot outline and the foot height were used, and in the second, the foot outline and the foot profile were used. The models were developed using 40 participants and then validated using a different set of 40 participants. Results show that each individual foot shape can be predicted within a mean absolute error of 1.36 mm for the left foot and 1.37 mm for the right foot using the first method, and within a mean absolute error of 1.02 mm for the left foot and 1.02 mm for the right foot using the second method. The second method shows somewhat improved accuracy even though it requires two images. Both the methods are relatively cheaper than using a scanner to determine the 3D foot shape for custom footwear design