Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring

2 Oct 2017Albert VilamalaKristoffer H. MadsenLars K. Hansen

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... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Sleep Stage Detection Sleep-EDF Deep CNN with transfer-learning Accuracy 81.3% # 3

Methods used in the Paper


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