Developing a sizing methodology for women's sports compression garments

Sports compression garments (SCGs) are skin-tight, elastic garments that are designed to apply pressure to the underlying body with the aim to improve exercise performance, shorten recovery and prevent injuries. For SCGs to function, pressure delivery needs to be controlled and consistent across individuals. This requires adequate garment fit. Current SCG research lacks garment considerations, leaving room for original and impactful contributions in the engineering and sizing of SCGs. The project aims to develop a methodology for the pattern grading and sizing of ready-to-wear women's SCGs with consistent pressure delivery.
Research objectives:
1. Analyse existing stretch pattern making and grading approaches.
2. Evaluate sizing methodologies used by SCG brands.
3. Identify key body measurements affecting pressure application.
4. Establish guidelines for the grading of SCGs to suit a population.
5. Define and validate a sizing methodology for women's SCGs with controlled pressure delivery.
Through experimentation and statistical analysis, this quantitative research project seeks to identify key body measurements affecting pressure delivery and establish guidelines for the grading of SCGs to suit a population. The project will make use of the latest technologies in 3D body scanning and virtual fit as well as established textile testing and pressure measurement methods.
The project will advance stretch pattern making and grading theory, which can enhance the functionality of SCGs and will be of commercial importance beyond the project focus (e.g. fit of wearables for health monitoring). The project complements existing research projects on body-informed pattern construction of woven, non-elastic garments in the Apparel Design Engineering research group.
This project fits into the EPSRC 'Engineering Design' research area under the 'Manufacturing the Future' theme because the advances in stretch pattern making and grading theory by this research will enable the development of automated pattern development processes for future made-to-measure manufacturing systems.