KonstantinosBarmpas/NeuroRVQ
NeuroRVQ: Multi-Scale EEG Tokenization for Generative Large Brainwave Models
This project helps neuroscientists and biomedical researchers analyze raw biosignals like EEG, EMG, and ECG data. It takes in these complex, noisy raw signals and transforms them into a structured, lower-dimensional 'neural grammar' of tokens. The output is a compact representation that captures essential temporal-spectral patterns, enabling more efficient and insightful analysis of brainwave and other biosignal data.
Use this if you need to transform high-dimensional and noisy EEG, EMG, or ECG data into a more manageable, tokenized format for advanced analysis or generative modeling.
Not ideal if you are looking for a simple, out-of-the-box classification solution without needing to understand or work with the underlying signal tokenization.
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27
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Language
Python
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Last pushed
Jan 23, 2026
Commits (30d)
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