Evaluating machine learning methods for detecting sleep arousal, bachelor thesis by Jacob Stachowicz and Anton Ivarsson (2019)
-
Updated
Apr 12, 2020 - Python
Evaluating machine learning methods for detecting sleep arousal, bachelor thesis by Jacob Stachowicz and Anton Ivarsson (2019)
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.
Add a description, image, and links to the polysomnography-data topic page so that developers can more easily learn about it.
To associate your repository with the polysomnography-data topic, visit your repo's landing page and select "manage topics."