文献类型：期刊文献

英文题名：A Kansei-inspired product design approach for the Liao Dynasty Pagoda: bridging cultural heritage and physiological signals

作者：Hong, Chunying[1];Liu, Yutong[2];Yu, Qiaoling[1];Yang, Chaoxiang[2]

机构：[1]Liaoning Univ Technol, Coll Culture Media & Art Design, Jinzhou, Peoples R China;[2]East China Univ Sci & Technol, Sch Art Design & Media, Shanghai 200237, Peoples R China

年份：2026

卷号：37

期号：1

起止页码：94

外文期刊名：JOURNAL OF ENGINEERING DESIGN

收录：;EI(收录号：20251118032286);WOS:【SCI-EXPANDED(收录号:WOS:001437550100001)】；

基金：This work was supported by the Scientific Research Fund of Liaoning Provincial Education Department: [Grant Number LJKR0228]; the Shanghai Pujiang Program: [Grant Number 2020PJC025];[Q1]the Chinese Universities Scientific Fund: [Grant Number JKZ01212202].

语种：英文

外文关键词：Kansei engineering; multimodal physiological signals; interactive genetic algorithm; cultural and creative product design; Liao Dynasty Pagoda culture

摘要：The protection and inheritance of regional cultural heritage are important for local economic development and artistic prosperity. Excellent cultural and creative products (CCPs) can better preserve and promote the unique allure of Liao Dynasty Pagoda culture. The CCP's current development process relies heavily on designers' subjective experiences, which can lead to a disconnect between CCPs and user needs. This work proposes a Kansei-inspired product design approach for the Liao Dynasty Pagoda culture by integrating multimodal physiological signals and the interactive genetic algorithm (IGA). First, multimodal physiological signalling experiments are conducted to identify cultural elements that resonate with users. Second, Kansei words are extracted from big data to understand users' emotional responses to CCPs. Factor analysis (FA) helps identify users' pivotal Kansei needs, whereas the analytic hierarchy process (AHP) determines the relative weights of these needs. Finally, the designer creates the initial morphological features on the basis of the extracted cultural elements. The interactive genetic algorithm with hesitancy-based interval individual fitness (IGA-HIIF) is then employed to construct the morphological design evolution system. This system predicts the most user-satisfying combination of design features, allowing the designer to refine, model, and render the final design.