Computer Science > Human-Computer Interaction
arXiv:2409.00962 (cs)
[Submitted on 2 Sep 2024]
Title:Mental-Gen: A Brain-Computer Interface-Based Interactive Method for Interior Space Generative Design
View a PDF of the paper titled Mental-Gen: A Brain-Computer Interface-Based Interactive Method for Interior Space Generative Design, by Yijiang Liu and 1 other authors
View PDFHTML (experimental)Abstract:Interior space design significantly influences residents' daily lives. However, the process often presents high barriers and complex reasoning for users, leading to semantic losses in articulating comprehensive requirements and communicating them to designers. This study proposes the Mental-Gen design method, which focuses on interpreting users' spatial design intentions at neural level and expressing them through generative AI models. We employed unsupervised learning methods to detect similarities in users' brainwave responses to different spatial features, assess the feasibility of BCI commands. We trained and refined generative AI models for each valuable design command. The command prediction process adopted the motor imagery paradigm from BCI research. We trained Support Vector Machine (SVM) models to predict design commands for different spatial features based on EEG features. The results indicate that the Mental-Gen method can effectively interpret design intentions through brainwave signals, assisting users in achieving satisfactory interior space designs using imagined commands.
| Comments: | 18 pages, 8 figures |
| Subjects: | Human-Computer Interaction (cs.HC) |
| ACM classes: | J.6 |
| Cite as: | arXiv:2409.00962 [cs.HC] |
| (orarXiv:2409.00962v1 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2409.00962 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Mental-Gen: A Brain-Computer Interface-Based Interactive Method for Interior Space Generative Design, by Yijiang Liu and 1 other authors
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