Epileptic seizure prediction using phase synchronization based on bivariate empirical mode decomposition

@article{Zheng2014EpilepticSP,
  title={Epileptic seizure prediction using phase synchronization based on bivariate empirical mode decomposition},
  author={Yang Zheng and Gang Wang and Kuo Li and Gang Bao and Jue Wang},
  journal={Clinical Neurophysiology},
  year={2014},
  volume={125},
  pages={1104-1111}
}
OBJECTIVE Epilepsy is a common neurological disorder with unpredictability. An effective algorithm for seizure prediction is important for the patients with refractory epilepsy. METHODS We proposed a seizure prediction method based on the phase synchronization information of neuronal electrical activities. Firstly, the instantaneous phase of the intracranial electroencephalograph (EEG) recordings was detected by the combination of bivariate empirical mode decomposition (BEMD) and Hilbert… CONTINUE READING

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