Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds.
Dihong JiangYu MaYuanyuan WangPublished in: Comput. Methods Programs Biomed. (2019)
Keyphrases
- multi channel
- physiological signals
- sleep stage
- feature space
- feature vectors
- feature set
- feature extraction
- riemannian manifolds
- pattern recognition
- heart rate
- feature selection
- sleep apnea
- daily life
- support vector machine
- training set
- machine learning
- image classification
- text classification
- support vector
- human subjects
- supervised learning
- euclidean space
- multi class classification
- emotion recognition
- low level
- multimedia