The digital preservation of intangible cultural heritage faces a significant challenge in bridging the sensory gap between physical artifacts and their virtual counterparts. This is particularly acute for textile heritage, where the complex interplay of anisotropic light reflection and non-linear mechanical deformation defines the craft. This study proposes a multimodal Human-Computer Interaction (HCI) framework designed to simulate the distinct material properties of rigid body (ceramics/porcelain) and soft body (embroidery/silk). We developed a differential rendering engine that utilizes a standard Cook-Torrance model for ceramic glazes and a modified Kajiya-Kay anisotropic shading model for silk fibers. Furthermore, a variable-stiffness haptic feedback algorithm was implemented to simulate the needle-fabric interaction forces. A comparative experiment with 120 participants evaluated the system across task performance, material recognition accuracy, and cognitive load (NASA-TLX). Results indicate that while visual fidelity is dominant for ceramic interactions (p < 0.05), the inclusion of force-feedback is critical for embroidery, reducing the operational error rate by 59% and significantly enhancing the perception of silk-like texture. This paper provides a validated engineering methodology for constructing high-fidelity digital textile heritage systems.

digital heritage, human-computer interaction, textile rendering, haptic feedback, embroidery