文献类型：期刊文献

英文题名：Perceptual design method for smart industrial robots based on virtual reality and synchronous quantitative physiological signals

作者：Xiao, Wangqun[1];Cheng, Jianxin[1]

机构：[1]East China Univ Sci & Technol, Sch Art Design & Media, Mailbox 286,130 Meilong Rd, Shanghai 200237, Peoples R China

年份：2020

卷号：16

期号：5

外文期刊名：INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS

收录：;EI(收录号：20202008668819);WOS:【SSCI(收录号:WOS:000536465700001)，SCI-EXPANDED(收录号:WOS:000536465700001)】；

基金：The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was financially supported by National Natural Science Foundation of China (51375014), Shanghai Design IV Top Subject (DC17013), and Ministry of Education Humanities and Social Science Youth Fund (18YJCZH197).

语种：英文

外文关键词：Industrial design; Kansei image; industrial robots; emotion recognition; physiological techniques

摘要：In the research of industrial robot design, designing using only the perceptual thinking and creativity of an industrial designer or overemphasizing the intervention of quantitative data research in the field of emotional cognition is relatively one sided. In this article, research on how to combine the above two aspects effectively will be conducted. The aim is to present a design method which provides artistic creativity and scientific support for industrial robot design. Therefore, a method for representing perceptual image spaces of industrial robots through pictures and semantics by evaluating the perceptual images and using statistical approaches such as factor analysis will be proposed. Perceptual design elements of industrial robots are decomposed from the perspective of style and color. After the quantitative type I analysis, the numerical relationships between the semantics of images and design elements are identified. Also, a method for mapping relationships between the perceptual image spaces and design elements of industrial robots is developed. After three-dimensional modeling and simulation, the semantic difference methods are used in combination with the emotional evaluation and measurement methods for physiological experiments such as eye tracking, skin conductance, heart rate, and electroencephalography experiments with the aid of virtual reality. Finally, a perceptual design method is extracted for smart industrial robots based on virtual reality and synchronous quantitative physiological signals.