Sleep Stage Prediction using Transformers
We propose a novel deep learning architecture on a single EEG channel using CNNs to extract features and Transformers to leverage neighboring temporal context to predict sleep stage label (Wake, REM, etc).
We propose a novel deep learning architecture on a single EEG channel using CNNs to extract features and Transformers to leverage neighboring temporal context to predict sleep stage label (Wake, REM, etc).