| id |
caadria2024_416 |
| authors |
Guo, Zhe, Zhang, Zixi, Zhang, Zihuan, Li, Ce and Kong, Yuhang |
| year |
2024 |
| title |
Perceptual Materialization for Space Interface: Exploring the Interactive Generation Design Method and Application of Space Interface via EEG Reveled Visual-Perception |
| source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 3, pp. 479–488 |
| doi |
https://doi.org/10.52842/conf.caadria.2024.3.479
|
| summary |
The primary objective of this research is to elucidate how individuals are immersed in the spatial visual ambiance, leading to the elicitation of perceptual emotions and the establishment of a feedback mechanism between visual-perception and generative design, which serves as the critical intermediary linking human behavior and spatial geometry. To achieve this goal, Electroencephalogram (EEG) signals have been chosen as the preferred modality. By establishing the integrated EEG device system and real-time interactive visual perception platform, this research explores an interactive design methodology for space interface design, drawing insights from visual perception as revealed through EEG data. Next, the method of integrating hardware and software to establish a visual human-computer interaction platform is explored in detail, and the data characteristics of joint nodes are analyzed. Furthermore, the spatial interface was selected as the object for EEG interaction generation, applying Voronoi planar pattern controlled by noise functions for complex interface geometry generation and attempting to convert data from 2D pixels to 3D solid mesh models. This research demonstrates significant potential for further exploration and development within creating more personalized interactive spatial experience. |
| keywords |
Generative Design, Human-Computer Interaction, EEG, Space Interface |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (2,401,817 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/11/17 22:05 |
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