Using Permutation Entropy to Measure the Changes in EEG Signals During Absence Seizures

In this paper, we propose to use permutation entropy to explore whether the changes in electroencephalogram (EEG) data can effectively distinguish different phases in human absence epilepsy, i.e., the seizure-free, the pre-seizure and seizure phases. Permutation entropy is applied to analyze the EEG...

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Bibliographic Details
Main Authors: Jing Li, Jiaqing Yan, Xianzeng Liu, Gaoxiang Ouyang
Format: Article
Language:English
Published: MDPI AG 2014-05-01
Series:Entropy
Subjects:
EEG
Online Access:http://www.mdpi.com/1099-4300/16/6/3049