Study on the Correlation between Hand Feeling and Physical Properties of Leather Fabrics for Clothing

Objective Hand feeling constitutes a critical attribute in evaluating the practicality of apparel products, as the tactile experience of fabrics directly influences consumer preference. However, the existing subjective evaluation methods for hand feeling suffer from a lack of quantitative description, while the objective evaluation approaches exhibit deviations in test correlation. To address these limitations, this study intends to analyze the correlations between hand feeling parameters—specifically stiffness, softness, and smoothness—and the conventional physical parameters of leather. The ultimate goal is to identify the associations between simple physical performance indices and hand feeling parameters.

Methods In this study, common plain, lychee-patterned, and Napa leather fabrics were selected as the tested samples. Physical parameters including mass per unit area, thickness, compression deformation, and friction resistance were measured using a digital display thickness gauge, leather softness tester, disc sampler, and friction resistance meter, respectively. Key parameters were identified based on the principal components derived from principal component analysis. Hand feeling parameters were quantified via a sensory performance evaluation tester, and regression models for each hand feeling parameter were established through multiple linear regression analysis. These analyses aim to clarify the correlations between simple physical performance indicators and hand feeling parameters.

Results The obtained model results indicate that the coefficients of determination (R²) for the three regression models—stiffness value, softness value, and smoothness value—all exceeded 0.8, demonstrating a strong correlation. In the stiffness value model, mass per unit area (p＜0.001) and thickness (p=0.010) exerted a highly significant effect, with both parameters showing a positive correlation with the material's stiffness. Additionally, friction resistance (p=0.040) exhibited a certain degree of significance in the model. The increase of coating layers on the leather surface altered the material's stiffness and surface morphology, thereby strengthening the correlation between frictional properties and stiffness value. In the softness value model, the p-value for compressive deformation was less than 0.001, indicating an extremely significant effect. The order of influence significance was determined as compressive deformation followed by thickness, suggesting that leather softness is closely associated with its compressive deformation performance. For the smoothness value model, leather friction resistance (p＜0.001) and thickness (p＜0.001) displayed a significant correlation. Specifically, the surface smoothness value of leather showed a significantly negative correlation with friction resistance. Namely, the smoother the surface, the lower the friction resistance. This relationship primarily depends on the micromorphology of the skin layer, including structural parameters such as surface pattern style, groove depth, and distribution uniformity.

Conclusions In this study, the correlation regression models for hand stiffness, softness, and smoothness were successfully developed based on precise measurements of physical parameters of leather, including mass, thickness, compression deformation, and frictional resistance per unit area. The primary variables influencing hand stiffness were found to be mass and thickness per unit area. Softness exhibited a positive correlation with compression deformation, but decreased significantly as thickness increased. Smoothness demonstrated a strong negative correlation with frictional resistance. By accurately quantifying these physical parameters of leather, an objective index system for the evaluation of hand feeling can be established, thereby providing a scientific basis for product development and market segmentation of leather goods.