On the use of time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals.
Larbi BoubchirSomaya Al-MáadeedAhmed BouridanePublished in: ICASSP (2014)
Keyphrases
- non stationary
- eeg signals
- epileptic seizures
- empirical mode decomposition
- extracted features
- signal processing
- feature set
- wavelet packet
- neural network
- machine learning
- hilbert transform
- classification accuracy
- gabor filters
- feature extraction
- blind source separation
- adaptive algorithms
- change point detection
- data mining