A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain

Elma O'Sullivan-Greene; Iven Mareels; Dean Freestone; Levin Kulhmann; Anthony Burkitt

doi:10.1109/IEMBS.2009.5333792

A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain

Elma O'Sullivan-Greene
, Iven Mareels
, Dean Freestone
, Levin Kulhmann
, Anthony Burkitt

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

21 Citations (Scopus)

Abstract

This paper presents a novel theoretical paradigm for epileptic seizure prediction based on a coupled oscillator model of brain dynamics. This model is used to investigate prediction methods capable of tracking the synchronization changes that may lead to a seizure. Previous results indicate that state-space reconstruction of a coupled oscillator model from an EEG-like signal is ill-posed, therefore, monitoring system synchronization via the EEG signal is unlikely to give advanced warning of imminent seizure activity. Through simulation, it is shown that synchronization tracking may still be viable using an input probing stimulus to actively seek information from the coupled oscillator network.

Original language	English
Title of host publication	Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Engineering the Future of Biomedicine, EMBC 2009
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	6428-6431
Number of pages	4
ISBN (Print)	9781424432967
DOIs	https://doi.org/10.1109/IEMBS.2009.5333792
Publication status	Published - 2009
Externally published	Yes
Event	International Conference of the IEEE Engineering in Medicine and Biology Society 2009 - The Hilton Minneapolis, Minneapolis, United States of America Duration: 3 Sept 2009 → 6 Sept 2009 Conference number: 31st https://ieeexplore.ieee.org/xpl/conhome/5307844/proceeding (Proceedings)

Conference

Conference	International Conference of the IEEE Engineering in Medicine and Biology Society 2009
Abbreviated title	EMBC 2009
Country/Territory	United States of America
City	Minneapolis
Period	3/09/09 → 6/09/09
Internet address	https://ieeexplore.ieee.org/xpl/conhome/5307844/proceeding (Proceedings)

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10.1109/IEMBS.2009.5333792

Cite this

O'Sullivan-Greene, E., Mareels, I., Freestone, D., Kulhmann, L., & Burkitt, A. (2009). A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 6428-6431). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IEMBS.2009.5333792

O'Sullivan-Greene, Elma ; Mareels, Iven ; Freestone, Dean et al. / A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE, Institute of Electrical and Electronics Engineers, 2009. pp. 6428-6431

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title = "A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain",

abstract = "This paper presents a novel theoretical paradigm for epileptic seizure prediction based on a coupled oscillator model of brain dynamics. This model is used to investigate prediction methods capable of tracking the synchronization changes that may lead to a seizure. Previous results indicate that state-space reconstruction of a coupled oscillator model from an EEG-like signal is ill-posed, therefore, monitoring system synchronization via the EEG signal is unlikely to give advanced warning of imminent seizure activity. Through simulation, it is shown that synchronization tracking may still be viable using an input probing stimulus to actively seek information from the coupled oscillator network.",

author = "Elma O'Sullivan-Greene and Iven Mareels and Dean Freestone and Levin Kulhmann and Anthony Burkitt",

note = "Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; International Conference of the IEEE Engineering in Medicine and Biology Society 2009, EMBC 2009 ; Conference date: 03-09-2009 Through 06-09-2009",

year = "2009",

doi = "10.1109/IEMBS.2009.5333792",

language = "English",

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booktitle = "Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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O'Sullivan-Greene, E, Mareels, I, Freestone, D, Kulhmann, L & Burkitt, A 2009, A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain. in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE, Institute of Electrical and Electronics Engineers, pp. 6428-6431, International Conference of the IEEE Engineering in Medicine and Biology Society 2009, Minneapolis, Minnesota, United States of America, 3/09/09. https://doi.org/10.1109/IEMBS.2009.5333792

A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain. / O'Sullivan-Greene, Elma; Mareels, Iven; Freestone, Dean et al.
Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE, Institute of Electrical and Electronics Engineers, 2009. p. 6428-6431.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AU - Mareels, Iven

AU - Freestone, Dean

AU - Kulhmann, Levin

AU - Burkitt, Anthony

N1 - Conference code: 31st

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AB - This paper presents a novel theoretical paradigm for epileptic seizure prediction based on a coupled oscillator model of brain dynamics. This model is used to investigate prediction methods capable of tracking the synchronization changes that may lead to a seizure. Previous results indicate that state-space reconstruction of a coupled oscillator model from an EEG-like signal is ill-posed, therefore, monitoring system synchronization via the EEG signal is unlikely to give advanced warning of imminent seizure activity. Through simulation, it is shown that synchronization tracking may still be viable using an input probing stimulus to actively seek information from the coupled oscillator network.

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DO - 10.1109/IEMBS.2009.5333792

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ER -

O'Sullivan-Greene E, Mareels I, Freestone D, Kulhmann L, Burkitt A. A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE, Institute of Electrical and Electronics Engineers. 2009. p. 6428-6431 doi: 10.1109/IEMBS.2009.5333792

A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain

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