The method addresses the issue of soft tissue movement during physical activity, which affects the fit and comfort of clothing, especially in sportswear and medical attire, said the research team.
It employs image recognition algorithms to assess tissue deformation with minimal error due to movement.
The research group, led by professor Joanne Yip from the School of Fashion and Textiles, has also created an analytical model that predicts tissue deformation.
The new model uses the Boussinesq solution, which is rooted in elastic theory and stress function methodology, explained the team.
The use of image recognition algorithms in this innovation allows for precise quantification of tissue deformation during physical activity.
According to the researchers, measurements that fail to accurately capture deformation, particularly when the body is in motion, frequently result in poorly fitting garments that compromise functionality.
The team notes that the method “tackles the issue by minimising motion artifacts and providing a systematic framework to correlate garment pressure with tissue response, which is vital for optimising wearables’ the biochemical efficacy”.
The integration of mechanical property testing into the new method allows for precise predictions of tissue deformation.
Tests comparing this method to body scanning measurements have shown deviations as small as 1.15mm in static conditions and 2.36mm during movement, providing designers with highly accurate data on soft tissue deformation, the team stated.
Professor Joanne Yip said: “Our technology is highly adaptable to compression-based garments, including sportswear such as leggings and functional medical wear like compression stockings and post-surgical garments. The analytical model can be tailored to different garment types by adjusting parameters like material mechanical properties and circumferential dimensions.”
During testing, the use of different materials, designs, and sizes used in sports leggings provided insights into how material properties affect fit and performance.
This framework enhances biomechanical simulation techniques for wearable tech and offers a “practical tool” for improving the ergonomics of sportswear.
It enables designers to create compression garments based on data, potentially enhancing athletic performance and reducing injury risks.
The new technology is not only feasible and cost-effective but can also be integrated into current CAD/CAM systems to streamline prototyping processes and diminish reliance on trial-and-error methods, the researchers stated.
The research "A novel anthropometric method to accurately evaluate tissue deformation" has been published in journal Frontiers in Bioengineering and Biotechnology.
