Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring
Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring
Sleep studies are important for diagnosing sleep disorders such as insomnia, narcolepsy or sleep apnea. They rely on manual scoring of sleep stages from raw polisomnography signals, which is a tedious visual task requiring the workload of highly trained professionals. Consequently, research efforts to purse for an automatic stage scoring …