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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2014-05-01
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Series: | Entropy |
Subjects: | |
Online Access: | http://www.mdpi.com/1099-4300/16/6/3049 |