Sleep-Wake Classification using Statistical Features Extracted from Photoplethysmographic Signals.
Mohammod Abdul MotinChandan Kumar KarmakarThomas PenzelMarimuthu PalaniswamiPublished in: EMBC (2019)
Keyphrases
- eeg signals
- extracted features
- classification accuracy
- feature extraction
- extracting features
- feature vectors
- textural features
- feature set
- sleep stage
- feature space
- classification method
- classification process
- classification models
- signal processing
- automatically extracted
- feature analysis
- support vector
- statistical analysis
- feature representation
- machine learning
- acoustic signals
- features extraction
- classification scheme
- benchmark datasets
- high dimensionality
- text classification
- pattern classification
- feature subset
- svm classifier
- sleep apnea
- image classification
- statistical information
- image features
- support vector machine
- low level
- pattern recognition
- decision trees
- correspondence analysis
- machine learning methods
- maximum entropy modeling
- feature weights
- spectral analysis
- machine learning algorithms
- training samples
- feature selection