Classification of Normal and Pre-Ictal EEG Signals Using Permutation Entropies and a Generalized Linear Model as a Classifier.
Francisco O. RedelicoFrancisco TraversaroMaría del Carmen GarcíaWalter SilvaOsvaldo Anibal RossoMarcelo R. RiskPublished in: Entropy (2017)
Keyphrases
- eeg signals
- linear model
- fold cross validation
- extracted features
- linear discriminant classifier
- signal processing
- brain computer interface
- regression model
- brain activity
- classification method
- motor imagery
- linear models
- classification algorithm
- support vector
- electrical activity
- class labels
- linear transformation
- classification scheme
- feature set
- least squares
- additive model
- pattern recognition
- decision trees
- epileptic seizures
- linear svm
- kernel density estimators
- decision boundary
- classification process
- classification rate
- image processing
- training data
- svm classifier
- training samples
- support vector machine
- feature space
- feature extraction
- regression trees
- three dimensional
- support vector machine svm
- brain signals
- event related potentials
- optical flow