Electroencephalogram signals classification for sleep-state decision - a Riemannian geometry approach.
Yili LiKon Max WongHubert de BruinPublished in: IET Signal Process. (2012)
Keyphrases
- eeg signals
- sleep stage
- classification accuracy
- signal processing
- decision rules
- eeg data
- pattern recognition
- decision makers
- healthy subjects
- feature selection
- brain activity
- text classification
- three dimensional
- decision making
- pattern classification
- feature extraction
- state space
- training set
- feature space
- classification algorithm
- acoustic signals
- machine learning
- multi class
- support vector machine
- independent component analysis
- support vector
- riemannian manifolds
- event related potentials