wjq-learning/EEGDiffuser
[Neurocomputing 2026] EEGDiffuser: Label-guided EEG signals synthesis via diffusion model for BCI applications
This project helps brain-computer interface (BCI) researchers and developers overcome the challenge of limited EEG data. It takes desired mental states or 'labels' as input and generates realistic, synthetic EEG signals. This allows for the creation of larger, more diverse datasets for training BCI systems.
Use this if you need to generate synthetic EEG data for specific mental states to expand your datasets for brain-computer interface (BCI) research or application development.
Not ideal if you are looking to analyze or interpret existing EEG signals rather than generate new ones.
Stars
9
Forks
2
Language
Python
License
MIT
Category
Last pushed
Jan 07, 2026
Commits (30d)
0
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