Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing.
Idiopathic epilepsy is characterized by generalized seizures with no apparent cause. One of its main problems is the lack of biomarkers to monitor the evolution of patients. The only tools they can use are limited to inspecting the amount of seizures during previous periods of time and assessing the...
Main Authors: | Jose Antonio Urigüen, Begoña García-Zapirain, Julio Artieda, Jorge Iriarte, Miguel Valencia |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5602520?pdf=render |
Similar Items
-
Permutation Entropy: Enhancing Discriminating Power by Using Relative Frequencies Vector of Ordinal Patterns Instead of Their Shannon Entropy
by: David Cuesta-Frau, et al.
Published: (2019-10-01) -
Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data
by: Jäntschi Lorentz, et al.
Published: (2017-08-01) -
Multiscale permutation Rényi entropy and its application for EEG signals.
by: Yinghuang Yin, et al.
Published: (2018-01-01) -
Measuring Instantaneous and Spectral Information Entropies by Shannon Entropy of Choi-Williams Distribution in the Context of Electroencephalography
by: Umberto Melia, et al.
Published: (2014-05-01) -
Shannon entropy and particle decays
by: Pedro Carrasco Millán, et al.
Published: (2018-05-01)