Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms.
Alexander Neergaard OlesenPoul JennumPaul E. PeppardEmmanuel MignotHelge B. D. SørensenPublished in: EMBC (2018)
Keyphrases
- sleep stage
- sleep apnea
- decision trees
- classification accuracy
- feature space
- machine learning
- class labels
- benchmark datasets
- pattern recognition
- statistical classification
- classification algorithm
- pattern classification
- classification models
- network structure
- network analysis
- automatic classification
- machine learning algorithms
- classification systems
- features extraction
- preprocessing
- support vector
- feature extraction
- classification scheme
- classification process
- svm classifier
- complex networks
- fully automatic
- classification method
- semi automatic
- support vector machine svm
- training samples
- image classification
- feature set
- support vector machine
- feature selection