Towards Domain Free Transformer for Generalized EEG Pre-training
A Python package to automatically identify artifacts in sleep EEG signals and detect data usability for sleep autoscoring
Sleep EEG Event Detector (SEED) model, a deep learning-based detector of sleep spindles and K-complexes
A Novel Adversarial Approach for EEG Dataset Refinement: Enhancing Generalization through Proximity-to-Boundary Scoring
Multichannel Sleep Spindle Detector for sleep EEG
Automated Sleep Stage Scoring using Deep Learing
An end-to-end deep learning pipeline for automatic sleep stage classification from polysomnography (PSG) signals. The system classifies 30-second EEG/EOG/EMG epochs into 5 AASM sleep stages (Wake, N1, N2, N3, REM) using a dual-input Teacher model (CNN + Transformer, ΞΊ=0.636) distilled into a lightweight Student model
π Run multiple spinners in Node.js effortlessly with Spindle, a lightweight CLI tool that ensures clear, simultaneous output without visual clutter.
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