Abstract:

Objective This study aims to investigate the quantitative relationship between the simulated pressure in a virtual try-on environment and actual dynamic pressure on real subjects with women's yoga leisure pants, so as to provide information for virtual simulation-based structural optimization in apparel design. Additionally, this study is set to investigate the dynamic patterns of garment pressure during specific yoga poses, conduct secondary optimization of prototype garments, and validated the pressure improvement effects based on these findings.

Method Virtual models and human subjects with standard 160/84A body measurements were selected, and some test clothes were made accordingly. Based on the material availability, virtual patterns were created using the DeepModa model, which were then developed into virtual clothes for virtual try-on. Next, different yoga poses were selected and a pressure measurement scheme was determined taking into account of the body's main stress points. Real pressure values measured on a clothed person and the pressure simulation values obtained using virtual simulation platform were recorded. Based on the data obtained, a mathematical relationship was established between the simulated and the practical pressure forces.

Results Pearson correlation analysis revealed significant positive correlations between the simulated pressure values and actual pressure measurements with the downward-facing dog pose (r=0.87) and the standing forward bend pose (r=0.72). Regression analysis indicated that the downward-facing dog pose and key points such as F₆, F₈ and B₅ had higher determination coefficients and that the regression model fits them well. However, the correlation was weakened for other complex movements, revealing the predictive limitations of the current virtual model in specific dynamic scenarios. Analysis of pressure distribution identified points F₃, F₆ and B₃ as high-pressure peak zones, primarily concentrated on the buttocks and inner thighs. In order to address this issue, the study implemented synergistic optimization of the structure and fabric. Additional darts and 0.5 cm of ease were added to the pattern structure along the stretch of the skin on the inner thigh of the front panel. The rear panel featured an M-shaped dart design with 0.5 cm of ease in the hip area, distributing pressure at point B₃ and creating a pressure-relief zone below the hips. This enhanced the fit along the hip line, improving alignment with the body's natural curves. Based on the significant correlation between fabric physical properties (e.g. tensile modulus is positively correlated with pressure, while resilience is negatively correlated with pressure) and pressure distribution, targeted improvements were made to fabric properties in the mid-anterior thigh and gluteal regions within the virtual environment. The test results showed a big decrease in pressure across all measurement points. In particular, when doing the downward-facing dog pose, the pressure at point B₃ dropped the most (10.64%), while that at point F₆ had the smallest decrease (6.67%). When the side angle was stretched, pressure at point F₆ had the biggest decrease in pressure (8.11%), and that at point F₃ had the smallest decrease (7.69%). This is mainly because the pressure is quite low at F₃, which limits improvement. Research findings indicated that these improvements made the body pressure more comfortable.

Conclusion When analyzing the relationship between virtual simulations and real-world pressure measurements in women's yoga loungewear, linear regression models demonstrate significant predictive power during specific static or low-amplitude poses such as downward facing dog pose. Based on this, the pattern structure and fabric properties were optimised to significantly improve pressure distribution at key stress points, effectively enhancing the garment's ability to adapt to dynamic human movement. This study further confirms the feasibility of using virtual simulation for guiding the optimization of garment structure and pressure comfort. Later studies might include infrared motion capture and non-linear models to create personalised multidimensional pressure transmission models, thus improving the precision of pressure simulation and prediction in garments.

Key words: yoga pants, casual pants pattern, clothing pressure, virtual fitting, virtual fabric simulation, virtual garment design, comfort quantification