Automatic Sleep Stage Classification using Marginal Hilbert Spectrum Features and a Convolutional Neural Network.
Wenshuai WangPan LiaoYi SunGuiping SuShiwei YeYan LiuPublished in: EMBC (2020)
Keyphrases
- convolutional neural network
- sleep stage
- classification accuracy
- feature vectors
- feature extraction
- feature set
- feature space
- classification method
- decision trees
- classification models
- classification process
- classification algorithm
- feature analysis
- features extraction
- face detection
- image classification
- svm classifier
- pattern classification
- support vector
- textural features
- benchmark datasets
- extracted features
- feature representation
- co occurrence
- feature weights
- feature construction
- decision tree classifiers
- discriminative features
- statistical classification
- classification scheme
- pattern recognition
- preprocessing
- data sets
- class labels
- sleep apnea
- machine learning
- neural network
- irrelevant features
- training data
- multiple features
- feature selection algorithms
- text classification
- knn