Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

Eulalie Joelle Ngamga; Stephan Bialonski; Norbert Marwan; Jürgen Kurths; Christian Geier; Klaus Lehnertz

doi:10.1016/j.physleta.2016.02.024

Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

Eulalie Joelle Ngamga, Stephan Bialonski, Norbert Marwan, Jürgen Kurths, Christian Geier, Klaus Lehnertz

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Abstract

We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.

Original language	English
Pages (from-to)	1419-1425
Number of pages	7
Journal	Physics Letters A
Volume	380
Issue number	16
Early online date	20 Feb 2016
DOIs	https://doi.org/10.1016/j.physleta.2016.02.024
Publication status	Published - 1 Apr 2016

Bibliographical note

7 pages, 4 figures

Acknowledgement
We are grateful to M. Riedl and G. Ansmann for fruitful discussions and critical comments on earlier versions of the manuscript. This work was supported by the Volkswagen Foundation (Grant Nos. 88461, 88462, 88463, 85390, 85391 and 85392).

Keywords

nlin.CD
physics.data-an
physics.med-ph

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abstract = "We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.",

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AU - Ngamga, Eulalie Joelle

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AU - Marwan, Norbert

AU - Kurths, Jürgen

AU - Geier, Christian

AU - Lehnertz, Klaus

N1 - 7 pages, 4 figures Acknowledgement We are grateful to M. Riedl and G. Ansmann for fruitful discussions and critical comments on earlier versions of the manuscript. This work was supported by the Volkswagen Foundation (Grant Nos. 88461, 88462, 88463, 85390, 85391 and 85392).

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N2 - We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.

AB - We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.

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Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

Abstract

Bibliographical note

Keywords

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