LimDoHyeon/EEG-LLM
Fine-tuned LLM for electroencephalography(EEG) data classification
This tool helps researchers and neuroscientists classify specific imagined movements directly from raw electroencephalography (EEG) data. You input EEG recordings from a participant performing cued motor imagery, and it outputs a classification indicating whether the participant imagined moving their left hand, right hand, foot, or tongue. This is for researchers studying brain-computer interfaces or motor imagery.
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Use this if you are a researcher or neuroscientist interested in exploring large language models (LLMs) for classifying motor imagery from EEG data.
Not ideal if you need a high-performance, production-ready EEG classification system, as traditional machine learning models currently outperform this LLM-based approach.
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Jupyter Notebook
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Last pushed
Jul 04, 2025
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