Product Styling Cognition Based on Kansei Engineering Theory and Implicit Measurement
Source abstract
Abstract
Effective product styling designs must increasingly address users’ emotional requirements. This study introduces a product styling design method combining electroencephalography (EEG) and eye tracking for multimodal measurement based on the Kansei engineering theory. The feasibility of determining a target image using a similarity calculation model is verified. An experimental paradigm based on implicit measures is presented for product styling cognition research. This paradigm involves determining the target image, sample selection, target image matching experiments, and product styling cognition experiments. Based on the combined EEG and eye-tracking measurements, insights into product-form cognition are deduced to provide a scientific basis for product-form innovation design. Notably, variations in event-related potential during user cognition of product styling are more evident in the product-styling perception phase than in the evaluation phase. In the styling perception phase, samples with “high match” with the target image elicit more pronounced EEG responses than those with “low match”. These findings demonstrate the viability of understanding product-form cognition through multimodal implicit measurements, addressing issues such as the pronounced subjectivity inherent in traditional methods. Furthermore, this approach provides a pioneering technique for Kansei engineering research and offers a methodology for multimodal implicit measurements of product innovation design.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Color perception and design · Multisensory perception and integration · Sensory Analysis and Statistical Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China
College of Mechatronic Engineering, North Minzu University, Yinchuan 750021, China
Key Laboratory of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, China
Funding
Scientific Research Project of Ningxia Education Department · Ningxia Natural Science Foundation · Ningxia Young Science and Technology Talent Support Project · Ningxia Industrial Design Center
References (57)
Show source-provided references
1. Designers as the determinants of design innovations10.1111/caim.12302 ↗
2. Krippendorff, K., and Butter, R. (1984). Product Semantics—Exploring the Symbolic Qualities of Form, University of Pennsylvania. Departmental Papers (ASC).
3. Lopez, O., Murillo, C., and Gonzalez, A. (2021). Systematic literature reviews in Kansei Engineering for product design—A comparative study from 1995 to 2020. Sensors, 21.10.3390/s21196532 ↗
4. Zhao, T.J., Zhang, X.Y., Zhang, H.C., and Meng, Y.F. (2023). A study on users’ attention distribution to product features under different emotions. Behav. Inf. Technol., 1–14.10.1080/0144929X.2023.2207681 ↗
5. Luo, S.J., Zhang, Y.F., Zhang, J., and Xu, J.H. (2020). A user biology preference prediction model based on the perceptual evaluations of designers for biologically inspired design. Symmetry, 12.10.3390/sym12111860 ↗
6. Product shape imagery design based on elliptical Fourier
7. Developing a user property metadata to support cognitive and emotional product design10.7838/jsebs.2016.21.4.069 ↗
8. An improved Kansei engineering method based on the mining of online product reviews10.1016/j.aej.2022.09.044 ↗
9. Gong, X., Guo, Z., and Xie, Z. (2022). Using Kansei engineering for the design thinking framework: Bamboo pen holder product design. Sustainability, 14.10.3390/su141710556 ↗
10. Group consumers’ preference recommendation algorithm model for online apparel’s colour based on Kansei engineering10.35530/IT.074.01.202268 ↗
11. Cognitive matching of design subjects in product form evolutionary design10.1155/2021/8456736 ↗
12. Investigating vehicle interior designs using models that evaluate user sensory experience and perceived value10.1017/S0890060419000246 ↗
13. Application of implicit measurement in social and personality psychology studies10.12677/AP.2018.81016 ↗
14. Towards an integrated framework to measure user engagement with interactive or physica1 products
15. Beyond self-report: A review of physiological and neuroscientific methods to investigate consumer behavior10.3389/fpsyg.2018.01655 ↗
16. Applying event related potentials to evaluate user preferences toward smartphone form design10.1016/j.ergon.2016.04.006 ↗
17. An study of electroencephalography cognitive model of product image10.3901/JME.2018.23.126 ↗
18. Advances in EEG-based design science research: Dimensions and methods
19. Current status and trends of EEG research in the field of general design
20. Relationship between eye fixation patterns and Kansei evaluation of 3D chair forms10.1016/j.displa.2017.09.002 ↗
21. The application of gaze heat maps in impression evaluation—Case study of Chinese college students evaluating historical souvenir stores in Japan10.5057/ijae.TJSKE-D-19-00019 ↗
22. Validation of evaluation model and evaluation indicators comprised Kansei engineering and eye movement with EEG: An example of medical nursing bed10.1007/s00542-018-4235-1 ↗
23. Target mining and recognition of product form innovation design based on image word similarity model10.1155/2022/3796734 ↗
24. Shinomura (2018). Hiroshiken, Iwanami Shoten.
25. Kansei engineering and comfort10.1016/S0169-8141(96)00022-4 ↗
26. Qiu, K., Su, J.N., Zhang, X.X., and Yang, W.J. (2020). Evaluation and balance of cognitive friction: Evaluation of product target image form combining entropy and game theory. Symmetry, 12.10.3390/sym12091398 ↗
27. Measuring cognitive complexity in parametric design
28. A fuzzy mapping method for Kansei needs interpretation considering the individual Kansei variance10.1007/s00163-021-00359-8 ↗
29. Applying Kansei/affective engineering methodologies in the design of social and service robots: A systematic review10.1007/s12369-020-00709-x ↗
30. An approach to website design for Turkish universities, based on the emotional responses of students10.1080/23311916.2020.1770915 ↗
31. Rough Kansei mining model for market-oriented product design10.1155/2020/6267031 ↗
32. The modified Kansei Engineering-based application for sustainable service design10.1016/j.ergon.2020.102985 ↗
33. Linking the Kansei food model to the general affective engineering model—An application on chocolate toffee fillings10.5057/ijae.IJAE-D-21-00024 ↗
34. Wang, Y., Zhao, Q.X., Chen, J., Wang, W.W., Yu, S.H., and Yang, X.Y. (2022). Color design decisions for ceramic products based on quantification of perceptual characteristics. Sensors, 22.10.3390/s22145415 ↗
35. A preliminary study of perceptual matching for the evaluation of beverage bottle design10.1016/j.ergon.2012.01.007 ↗
36. Castiblanco Jimenez, I.A., Gomez Acevedo, J.S., Olivetti, E.C., Marcolin, F., Ulrich, L., Moos, S., and Vezzetti, E. (2023). User engagement comparison between advergames and traditional advertising using EEG: Does the user’s engagement influence purchase intention?. Electronics, 12.10.3390/electronics12010122 ↗
37. Understanding consumer physiological and emotional responses to food products using electroencephalography (EEG)10.1016/j.tifs.2019.09.018 ↗
38. How is the neural response to the design of experience goods related to personalized preference? An implicit view10.3389/fnins.2018.00760 ↗
39. Low-order webpage layout in online shopping facilitates purchase decisions: Evidence from event-related potentials10.2147/PRBM.S238581 ↗
40. Dual-processing accounts of reasoning, judgment, and social cognition10.1146/annurev.psych.59.103006.093629 ↗
41. Distinguishing and quantifying the visual aesthetics of a product: An integrated approach of eye-tracking and EEG10.1016/j.ergon.2019.02.006 ↗
42. A green-IKE inference system based on grey neural network model for humanized sustainable feeling assessment about products
43. A morphing method for shape generation and image prediction in product design10.1016/S0142-694X(01)00028-X ↗
44. A hybrid approach for paraphrase identification based on knowledge-enriched semantic heuristics10.1007/s10579-019-09466-4 ↗
45. Chinese semantic document classification based on strategies of semantic similarity computation and correlation analysis10.1016/j.websem.2020.100578 ↗
46. A context-based disambiguation model for sentiment concepts using a bag-of-concepts approach10.1007/s12559-020-09729-1 ↗
47. Mei, J.J. (1983). TongYiCi CiLin, Shanghai Dictionary Publishing House.
48. Che, W., Feng, Y., Qin, L., and Liu, T. (2021). An open-source neural language technology platform for Chinese. arXiv.10.18653/v1/2021.emnlp-demo.6 ↗
49. Customer segmentation using K-means clustering and the hybrid particle swarm optimization algorithm10.1093/comjnl/bxab206 ↗
50. A study affective factor extraction using methodology for Kansei engineering
51. Huang, Y., and Pan, Y. (2021). Discovery and extraction of cultural traits in intangible cultural heritages based on Kansei engineering: Taking Zhuang brocade weaving techniques as an example. Appl. Sci., 11.10.3390/app112311403 ↗
52. Using event-related potentials to identify user’s moods induced by product color stimuli with different attributes10.1016/j.displa.2022.102198 ↗
53. Prediction of product design decision Making: An investigation of eye movements and EEG features10.1016/j.aei.2020.101095 ↗
54. Research on the construction method of kansei image prediction model based on cognition of EEG and ET10.1007/s12008-020-00651-2 ↗
55. The effect of product image dynamism on purchase intention for online aquatic product shopping: An EEG study10.2147/PRBM.S313742 ↗
56. Kalantari, S., Cruz-Garza, J., Xu, T., Mostafavi, A., and Gao, E. (2023). Store layout design and consumer response: A behavioural and EEG study. Build. Res. Inf.10.1080/09613218.2023.2201415 ↗
57. Image visualization: Dynamic and static images generate users’ visual cognitive experience using eye-tracking technology10.1016/j.displa.2022.102175 ↗