Bio: Edith Gazzuolo is an academic researcher from Minneapolis College of Art and Design. The author has an hindex of 1, co-authored 1 publications receiving 21 citations.
TL;DR: Traditional linear measurements were compared with measurements of frontal and lateral view photographs for usefulness in determining pattern dimensions for the upper torso of the female body form, and photographic measurements were more accurate in predicting others, particularly pattern angles.
Abstract: Traditional linear measurements (lengths and circumferences taken over the body surface with a tape measure) were compared with measurements of frontal and lateral view photographs for usefulness in determining pattern dimensions for the upper torso of the female body form. The statistical regression models developed indicated that, while linear measurements provided slightly more accuracy in predicting a few of the pattern dimensions, the photographic measurements were more accurate in predicting others, particularly pattern angles. Photographic measurements hold promise as an alternative to the more intrusive linear measurements for predicting pattern dimensions.
TL;DR: Many methods have been developed to measure the human body in an effort to capture its dimensions for clothing as mentioned in this paper, which is important in developing garments to fit the body, and syst...
Abstract: Many methods have been developed to measure the body in an effort to capture its dimensions for clothing. Measuring the human body has been important in developing garments tofit the body, and syst...
TL;DR: It is concluded that threshold levels at which fit differences can be perceived can be established for different areas of the body, and that perceptible fit variations can be quite small.
Abstract: The development of new computer technologies designed to custom-fit apparel has created a need for quantification of apparel fit characteristics. Fit perception and preference data are needed to improve sizing for ready-to-wear and custom-fitted apparel. Tactile responses of subjects to the fit of pants were investigated using an adaptation of an American Society for Testing and Materials (ASTM) sensory perception test. The test was designed to establish thresholds in apparel fit: that is, the smallest difference in garment dimensions that can be consistently perceived and identified. The test samples for the study were a set of 15 pants, which varied in size, made for each participant from precise computer-generated patterns. Four female experts in apparel fit, who comprised the subject panel, each recorded their responses to these pants compared to a control. Control pants were custom-fitted to each panel member; the remaining pants in each set varied from the control by 0.5 to 1.5 cm at a single location (waist, hips, or crotch length). When the pants were presented in a blind test, the panel perceived differences as small as 0.5 cm in pants waist size from the control. Differences of 1.5 cm were perceptible at the hip and crotch. The subject's level of acceptance of the fit variations in the pants was then judged using a preference test. This test revealed differences among individual subjects in the acceptability of fit variations in waist and crotch dimensions; judgements of the acceptability of hip variations were more consistent among the subjects. Judging from the results of this testing, it is concluded that threshold levels at which fit differences can be perceived can be established for different areas of the body, and that perceptible fit variations can be quite small. This testing also showed that individuals vary in their tolerance for fit variations at different locations on the body.
TL;DR: In this article, the authors present a body scan based approach for sizing and fitting of garments, which is used in the fashion retail environment to enable consumers to engage with fit online.
Abstract: Achieving well fitting garments matters to consumers and, therefore, to product development teams, garment manufacturers and fashion retailers when creating clothing that fits and functions both for individuals and for a retailer's target populations. New tools and software for body scanning and product development enhance the ways that sizing and fitting can be addressed; they provide improved methods for classifying and analysing the human body and new ways of garment prototyping through virtual product development.Recent technological developments place a growing demand on product development teams to reconsider their approach to prototyping, sizing and fitting. Significant, related changes are also being made in the fashion retail environment, including innovations in virtual fit to enable consumers to engage with fit online. For best effect in the short term, such advances need to relate well to existing manufacturing practices and to the methods that have, over many years, become embedded by practit...
TL;DR: The need for anthropometric research to design for special groups, such as children, the elderly and people with disabilities, and methodological issues that should be considered in future research are emphasised.
Abstract: Anthropometry is a key element of ergonomic studies for addressing the problem of fitting the tasks/products to user characteristics, but there is a gap between anthropometric data and their application for designing ergonomic products and environments. This research was conducted to review the literature on the methodology and applications of anthropometry for the ergonomic design of products and environments, and to identify where further research is needed to improve its application and evaluation protocols. One hundred and sixteen papers meeting the inclusion criteria were reviewed. Although a number of anthropometric investigations have been conducted to improve the design of products/environments for different users, further research seems to be necessary, particularly for special groups, such as children, the elderly and people with disabilities. Different anthropometric measurement methods/techniques and fitting criteria are discussed regarding their applicability for various design applications. This review also highlights methodological issues (sampling considerations and prototype evaluation and testing) that should be considered in future research to ensure a user-centred approach of the design process. Practitioner Summary: A literature review was conducted on the methodology and applications of anthropometry for the ergonomic design of products/environments. This review emphasises the need for anthropometric research to design for special groups, such as children, the elderly and people with disabilities, and methodological issues that should be considered in future research. Abbreviations: 1D: one-dimensional; 2D: two-dimensional; 3D: three-dimensional; HF/E: Human Factors/Ergonomics; PCA: Principal Components Analysis; CA: Cluster Analysis; DHM: Digital Human Modelling.
01 Jan 2004
TL;DR: In this paper, the authors developed a female figure identification technique (FFIT for Apparel) based on body scan data to classify females based on their body shapes and use the nine body shapes identified in the software to implement mass customization strategies in the apparel retail industry.
Abstract: The software “Female Figure Identification Technique (FFIT) for Apparel’ was developed at North Carolina State University, College of Textiles as a starting point to classify females based on their body shapes. The nine body shapes identified in the software could be used effectively to implement mass customization strategies in the apparel retail industry. In addition the shapes could be used in developing new sizing standards for the apparel industry. The software was built using a convenience sample of 253 female subjects primarily from the state of North Carolina. This study was developed to validate the software using a larger population. Multivariate statistical methods of discriminant analysis and Multivariate Analysis of Variance (MANOVA) were used for the validation process. The percentage accuracy of the FFIT for Apparel © software was found to be around 90% and was better than the discriminant function developed from the training sample used to build the software. During the validation process, the scans were visually analyzed and many interesting details throwing light on the influence of body scan data on shape analysis were found.