Characterizing the EEG Features of Inspiring Designers with Functional Terms
This paper constructed an inspiring database containing functional terms, which was taken as the source of external stimuli provided to designers. We obtained EEG of two groups of designers based on design experiment. One group is provided with closely related functional terms, while another group is provided without stimuli. After processing these EEG, we found that there are different characteristics in the EEG for the two groups of designers. Our experimental results provide a basis for the study of design thinking using EEG.
KeywordsEEG features Inspiring designer Functional term
The authors would like to thank the anonymous reviewers for their valuable comments and thank the strong support provided by National Natural Science Foundation of China (NSFC 51505032) and Beijing Natural Science Foundation (BJNSF 3172028).
- 1.Howard, T.J.: Information management for creative stimuli in engineering design. University of Bath (2008)Google Scholar
- 5.Li, Y., Wang, J., Li, X., et al.: Creative thinking and computer aided product innovation design and research. Comput. Integr. Manuf. Syst. 9(12), 1092–1096 (2003)Google Scholar
- 6.Miller, S.R., Toh, C.A.: The impact of example modality and physical interactions on design creativity. J. Mech. Des. 136(136), 543–552 (2014)Google Scholar
- 7.Sarkar, P., Chakrabarti, A.: The effect of representation of triggers on design outcomes. AI EDAM: Artif. Intell. Eng. Des. Anal. Manuf. 22(2), 101–116 (2008)Google Scholar
- 8.Linsey, J.S., Wood, K.L., Markman, A.B.: Modality and representation in analogy. AI EDAM 22(2), 85–100 (2008)Google Scholar
- 12.Wang, N.: Brain Cognition and Network Based on EEG Signal. Beijing University of Science and Technology Information (2015)Google Scholar
- 13.Wood, K.L.: Functional analysis: a fundamental empirical study for reverse engineering, benchmarking and redesign. ASME DETC (1997)Google Scholar
- 16.Meng, X., Ouyang, K.: Several nonlinear dynamic analysis methods of EEG signal. Beijing Biomed. Eng. 3, 135–140 (1997)Google Scholar
- 19.Geyer, S., Dinse, J.: Brodmann’s Areas. Reference Module in Neuroscience and Biobehavioral Psychology (2017)Google Scholar