End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets
End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets
Humans approximately spend a third of their life sleeping, which makes monitoring sleep an integral part of well-being. In this paper, a 34-layer deep residual ConvNet architecture for end-to-end sleep staging is proposed. The network takes raw single channel electroencephalogram (Fpz-Cz) signal as input and yields hypnogram annotations for each …