A Brain-Computer Interface-Based Interactive Method for Interior Space Generative Design.
Date: 2024.03-2024.07
Type: Personal Project
Feature:Brain-computer interaction; AI-assisted design; HCI development
Background: Users can now easily draft their design ideas using AI tools. However, the generated
results are subject to randomness due to prompts and model variations, often failing
to capture the core concepts. Additionally, semantic mismatches during Iteration
hinder further exploration of users' inner design thoughts.
Method: I performed unsupervised distance analysis on participants' EEG data while they viewed
various interior design concepts to identify spatial features suitable for BCI commands.
Subsequently, I trained an SVM model to recognize these design commands from the EEG signals.
Related Paper: https://arxiv.org/abs/2409.00962