Body data-driven garment pattern construction in digital fashion innovations: a review

Body data are indispensable for garment pattern construction, not only influencing garment quality but also shaping the competitiveness of apparel enterprises and driving the digital transformation of the fashion industry. Traditional pattern construction practices primarily rely on a limited number of one-dimensional (1D) measurements, with less consideration given to higher-dimensional body data, such as three-dimensional (3D) shapes and four-dimensional (4D) motion information. This underutilization of advanced anthropometric data reflects the technological limitations of past eras. With the rapid advancement of digital technologies, cutting-edge anthropometry and digital tools have significantly enhanced the integration of body data into pattern construction. To comprehensively understand the utilization of body data in digital pattern construction, as well as to clarify the current technological landscape and future directions, this review provides a thorough analysis of the evolution of body data utilization and facilitators in pattern construction, pattern construction methods based on multidimensional body data (1D–4D), as well as the distinctions and applications of these approaches. Furthermore, this review offers a comprehensive examination of the prospects and challenges in pattern construction, considering key aspects such as dynamic pattern construction, AI-driven generation, CAD system integration, and emerging business opportunities. It underscores the scientific and innovative potential of high-dimensional 4D body data and AI-powered tools in advancing modern garment pattern construction. By highlighting these developments, this review aims to provide researchers with valuable insights, enabling them to anticipate and explore uncharted possibilities in the field.