| Abstract: | The lateral body shape is a critical determiner of the fit of garments. Either visual assessment or statistical analysis methods have been used to classify the lateral body types. These methods are limited to some extent since various anthropometric features inherently coexist and interact in a human body shape. This study aims to develop objective criteria for the classification of upper lateral body shapes integrating visual assessment and statistical analysis. The three‐dimensional scan data of 246 women between 18 and 49 years old were visually classified into four lateral body shapes by an expert panel. In addition, the back space and lateral angles extracted from the scan data were employed for further statistical analyses. Multinomial logistic regressions were used to develop logit models for lateral body types. It was concluded that the resulting logit models could classify lateral body types and calculate the probability of a set of body scan data being classified as a certain lateral body type. It is expected that this probability might be a guideline to quantify the characteristics of the lateral body shape in the apparel industry. © 2010 Wiley Periodicals, Inc. |
