3D female breasts aging patterns integrating age and BMI for ergonomic fashion design

Abstract

Understanding how breast morphology changes with age and body mass index (BMI) is essential for developing ergonomically designed breast-related fashion products that ensure better fit and comfort. However, creating accurate 3D aging models is challenging due to the scarcity of comprehensive data, particularly for specific populations like Chinese women. This paper presents a novel framework for modeling 3D aging patterns in Chinese female breasts by integrating both age and BMI as key variables. We constructed a 3D statistical shape model (SSM) from scans of 305 Chinese women (aged 20–70 years, BMI 16.1–36.9 kg/m²) to capture core geometric variations. Moving beyond traditional linear methods, we employed a Gaussian kernel-based locally weighted partial least squares regression (LW-PLSR) to model the complex, nonlinear relationships between demographic and anthropometric factors and breast shape. To our knowledge, this is the first study to generate a 3D breast aging model that explicitly incorporates BMI alongside age for any population. The resulting model accurately captures changes in breast morphology and provides objective, data-driven tools for the fashion and textiles industries. It also offers practical geometric insights to inspire designers, manufacturers, and researchers to advance inclusive fashion design for women across a comprehensive range of ages and body sizes, thereby improving apparel comfort, fit, and functionality.