If you want to contribute, feel free to fork the repo and open a PR.
You can also DM me or share your GitHub username when you submit changes.
I built an ML project on EEG (brain signals) for motor imagery classification.
Initial results looked good — but the evaluation was flawed (subject leakage, weak baselines, unfair comparisons).
So I rebuilt it:
• Subject-aware evaluation (no leakage)
• PCA for fair feature comparison
• Statistical testing
• Cross-dataset evaluation (PhysioNet ↔ BCI2a)
Result:
Models work within a dataset, but fail to generalise across datasets.
The original FFT > band power > time-domain claim does not hold.
This repo is now a reproducible baseline highlighting that issue.
Research Paper + Repo link: https://doi.org/10.5281/zenodo.19956764