Application of EEG Technology in Kansei Engineering

Authors

  • Xiangyu Li

DOI:

https://doi.org/10.54691/jzd29s57

Keywords:

EEG Technology; Kansei Engineering; Industrial Design.

Abstract

This paper introduces the theory of EEG technology, operation process and the concept of Kansei Engineering, and discusses how EEG technology can be applied to Kansei Engineering. By recording the EEG signals of participants and analyzing the changes of these signals, EEG technology can help designers to understand the needs and responses of users more deeply, thus optimizing product design and improving user experience and market competitiveness. And the future combination of the two in more aspects is prospected.

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References

Li Yingjie, Qiu Yihong, Zhu Yisheng. EEG signal analysis method and its application [M]. Beijing: Science Press, 2009.

FINK A, BENEDEK M. EEG Alpha Power and Creative Ideation[J]. Neuroscience and Biobehavioral Reviews, 2014 (44): 111-123.

SEBASTIANI L, SIMONI A, GEMIGNANI A, et al.Autonomicand EEG correlates of emotional imagery in subjects with different hypnotic susceptibility[J]. Brain Research Bulletin, 2003, 60( 1 /2) : 151-160.

Deng Yaqian, Lin Li, Guo Zhuen, et al. Sensibility evaluation of automobile interior color with EEG combined with behavioral indicators [J]. Mechanical Science and Technology, 2023,42 (05): 747-754. DOI: 10.13433/j.cnki.1003-1003.10080888806.

Yang Cheng, Ceng Jing, Chen Chen, et al. Exploring the influence of appearance characteristics on product identification based on EEG [J]. Journal of Tongji University (Natural Science Edition), 2020, 48(09):1385-1394.

Tang Bangbei, Guo Gang, Wang Kai, et al. User Experience Selection of Automotive Industry Design Based on Eye Movement and EEG [J]. Computer Integrated Manufacturing System, 2015, 21(6): 1449-1459.

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Published

2024-03-22

Issue

Section

Articles

How to Cite

Li, X. (2024). Application of EEG Technology in Kansei Engineering. Frontiers in Science and Engineering, 4(3), 73-77. https://doi.org/10.54691/jzd29s57