Statistical spectral feature extraction for classification of epileptic EEG signals

@article{Choe2010StatisticalSF,
  title={Statistical spectral feature extraction for classification of epileptic EEG signals},
  author={Seong-Hyeon Choe and Yoon Gi Chung and Sung-Phil Kim},
  journal={2010 International Conference on Machine Learning and Cybernetics},
  year={2010},
  volume={6},
  pages={3180-3185}
}
Discrimination of epileptic activity in the electroencephalogram (EEG) signals continuously recorded from the brain may facilitate the effective and accurate diagnosis of epilepsy. This paper proposes a new statistical method combined with a simple classification algorithm that can discriminate epileptic EEG signals from normal signals. The statistical method extracts most significant spectral features by maximizing statistical distance between the epileptic and the normal power spectrums. The… CONTINUE READING