Noisy EEG signals classification based on entropy metrics. Performance assessment using first and second generation statistics.
David Cuesta-FrauPau Miró-MartínezJorge Jordán NúñezSandra Oltra-CrespoAntonio Molina-PicóPublished in: Comput. Biol. Medicine (2017)
Keyphrases
- eeg signals
- eeg data
- motor imagery
- brain computer interface
- pattern recognition
- signal processing
- classification accuracy
- image classification
- brain activity
- support vector
- feature space
- extracted features
- computer vision
- kernel density estimators
- entropy measure
- human brain
- independent component analysis
- support vector machine svm
- supervised learning
- decision trees
- healthy subjects
- image processing
- feature selection
- neural network