Integrating Ethnic Art Elements into Smart Textile Interaction Design for Cultural Expression and User Experience

Yingfang Xu · idd3 · 2026

This study presents a framework for integrating ethnic art into smart textile design to enhance cultural expression and user experience.

High AI ConfidenceStrong SourceWorking PrototypeDevelopment Stage

Plain English summary

The research develops a structured framework for incorporating ethnic art into smart textile interaction design. It focuses on enhancing cultural expression and user experience through a systematic approach that includes cultural decomposition and experience mapping. A prototype inspired by Miao embroidery was created and tested with users to evaluate its effectiveness.

Why this matters

This research addresses the gap in smart textile applications that often overlook cultural content in favor of technical features. By integrating cultural elements, it enhances user engagement and satisfaction, making smart textiles more meaningful and relevant in diverse contexts.

Key findings

  • The proposed framework improves cultural narrative recognition accuracy.
  • User experience satisfaction is significantly higher with the framework-guided design.
  • The framework includes cultural decomposition and adaptive optimization.
  • A prototype based on Miao embroidery was successfully developed.
  • The study involved a mixed-method user evaluation with 60 participants.

What's new

The study introduces a structured design-and-evaluation framework specifically for integrating cultural elements into smart textile interaction, moving beyond mere visual adaptation.

Limitations

The abstract does not detail the specific limitations of the framework or the prototype's performance in varied contexts.

Commercial context

The framework has been empirically tested with a prototype, indicating potential for further development and application in the market.

Publication

Publisher
idd3
Publication date
April 25, 2026
Research type
Paper

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Method note: Summaries and ratings on this page are generated by AI from the abstract only. Read the original paper for full context. · Model: gpt-4o-mini-2024-07-18