LimDoHyeon/EEG-LLM

Fine-tuned LLM for electroencephalography(EEG) data classification

25
/ 100
Experimental

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.

No commits in the last 6 months.

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.

neuroscience brain-computer-interface EEG-analysis motor-imagery biomedical-research
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 10 / 25

How are scores calculated?

Stars

14

Forks

2

Language

Jupyter Notebook

License

Category

llm-fine-tuning

Last pushed

Jul 04, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/LimDoHyeon/EEG-LLM"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.