Sleep stage classification from raw EEG/EOG using a spatial-temporal CNN (Chambon 2018 variant). Trained on PhysioNet SleepEDF-78 with MNE-Python preprocessing, ICA artifact removal, and PyTorch. Achieves ~0.72 Cohen's Kappa on subject-wise held-out test set.
deep-learning cnn pytorch eeg convolutional-neural-networks physionet mne-python ica eeg-classification sleep-staging mlflow polysomnography polysomnography-data sleep-edf biosignal-processing chambon-2018
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Updated
Apr 10, 2026 - Python