3D Body Data Analysis of Women’s Top Sizes Aged 18-25 Years

Few studies in China use age as a criterion for garment size analysis in female body shape research. This project addresses the challenge of designing clothing that fits young women aged 18-25 by examining their upper body shapes. Combining Martin measurements and three-dimensional scanning, data on 198 women’s body characteristics were collected, and morphological changes in their upper bodies were analysed.The upper body shapes were categorised into four types, and representative silhouettes were compared. The body shape classification results were combined with the national chest-waist difference classification method. The primary control variables for women’s shirt sizing were determined, and a linear regression equation was used to obtain the segmented values for each control variable.Ultimately, a specification system for women’s shirt sizes was established, providing a novel approach to research on body types and sizing systems.

Authors

Institutions

Publication Details

Journal
Journal of Fiber Bioengineering and Informatics
Published
2024-12-11
DOI
https://doi.org/10.3993/jfbim03051
Primary Topic
Consumer Perception and Purchasing Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

3D Body Data Analysis of Women’s Top Sizes Aged 18-25 Years

Ruo-Dan Pang, Ming-Hai Cui null, Yan-Xia Xu
Journal of Fiber Bioengineering and Informatics
Consumer Perception and Purchasing Behavior
article

3D Body Data Analysis of Women’s Top Sizes Aged 18-25 Years

Ruo-Dan Pang, Ming-Hai Cui null, Yan-Xia Xu
article en

Abstract

Few studies in China use age as a criterion for garment size analysis in female body shape research. This project addresses the challenge of designing clothing that fits young women aged 18-25 by examining their upper body shapes. Combining Martin measurements and three-dimensional scanning, data on 198 women’s body characteristics were collected, and morphological changes in their upper bodies were analysed.The upper body shapes were categorised into four types, and representative silhouettes were compared. The body shape classification results were combined with the national chest-waist difference classification method. The primary control variables for women’s shirt sizing were determined, and a linear regression equation was used to obtain the segmented values for each control variable.Ultimately, a specification system for women’s shirt sizes was established, providing a novel approach to research on body types and sizing systems.

Journal of Fiber Bioengineering and InformaticsVol. 17(4)
Beijing Institute of Fashion Technology (CN)
Gender equality
Openalex Percentile: Top 67%
Consumer Perception and Purchasing Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.