Title: Modelling affective aspects of human-artefact interaction based on Kansei engineering: application to the hairdryer domain

Authors: Mingcai Hu; Fu Guo; Zenggen Ren; Hao Shao; Vincent G. Duffy

Addresses: Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' School of Industrial Engineering, College of Engineering, Purdue University, Grissom Hall, 315 N. Grant Street, West Lafayette, Indiana 47907-2023, USA

Abstract: Recently in ergonomics and human factors community, there have been calls for incorporating affective aspects, such as pleasure and aesthetics, for product development. This study presents a systematic approach to modelling Kansei, which is users' subjective feeling and impression, by combining variable precision rough sets (VPRS) and association rule mining. The design element reducts corresponding to each Kansei attribute are firstly extracted using β-partition quality-based attribute reduction algorithm. Subsequently, the Apriori algorithm was adopted to induce middle-order association rules. The empirical results involving appearance design of hairdryer domain demonstrate the usefulness of the adoption of VPRS. The induced rules can serve the purpose of working memory and inference engine of a virtual Kansei engineering system, which provides a potential research line for modelling affective aspects of human-artefact interaction in the community of digital human modelling.

Keywords: affective aspects; Kansei modelling; human-artefact interaction; Kansei engineering; affective design; variable precision rough sets; VPRS.

DOI: 10.1504/IJDH.2023.133034

International Journal of the Digital Human, 2023 Vol.2 No.3, pp.143 - 159

Received: 08 May 2019
Accepted: 23 Jan 2020
Published online: 25 Aug 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article