Topological seizure origin detection in electroencephalographic signals

Yuan Wang; Hernando Ombao; Moo K. Chung

doi:10.1109/ISBI.2015.7163885

Topological seizure origin detection in electroencephalographic signals

Yuan Wang, Hernando Ombao, Moo K. Chung

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

9 Scopus citations

Abstract

We propose a method for detecting seizure origin in epileptic electroencephalographic (EEG) data based on a novel multi-scale topological technique called persistent homology (PH). Among several PH descriptors, persistence landscape (PL) possesses many desirable properties for rigorous statistical inference. By building PLs on EEG epilepsy signals smoothed by a weighted Fourier series (WFS) expansion, we compared the before and during phases of a seizure attack in a patient diagnosed with left temporal epilepsy and successfully identified site T3 as the origin of the seizure attack.

Original language	English (US)
Title of host publication	2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
Publisher	IEEE Computer Society
Pages	351-354
Number of pages	4
ISBN (Electronic)	9781479923748
DOIs	https://doi.org/10.1109/ISBI.2015.7163885
State	Published - Jul 21 2015
Externally published	Yes
Event	12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States Duration: Apr 16 2015 → Apr 19 2015

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2015-July
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Other

Other	12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/Territory	United States
City	Brooklyn
Period	04/16/15 → 04/19/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

EEG
epilepsy
persistence landscape
persistent homology

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI.2015.7163885

Cite this

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title = "Topological seizure origin detection in electroencephalographic signals",

abstract = "We propose a method for detecting seizure origin in epileptic electroencephalographic (EEG) data based on a novel multi-scale topological technique called persistent homology (PH). Among several PH descriptors, persistence landscape (PL) possesses many desirable properties for rigorous statistical inference. By building PLs on EEG epilepsy signals smoothed by a weighted Fourier series (WFS) expansion, we compared the before and during phases of a seizure attack in a patient diagnosed with left temporal epilepsy and successfully identified site T3 as the origin of the seizure attack.",

keywords = "EEG, epilepsy, persistence landscape, persistent homology",

author = "Yuan Wang and Hernando Ombao and Chung, {Moo K.}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",

year = "2015",

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doi = "10.1109/ISBI.2015.7163885",

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Wang, Y, Ombao, H & Chung, MK 2015, Topological seizure origin detection in electroencephalographic signals. in 2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015., 7163885, Proceedings - International Symposium on Biomedical Imaging, vol. 2015-July, IEEE Computer Society, pp. 351-354, 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Brooklyn, United States, 04/16/15. https://doi.org/10.1109/ISBI.2015.7163885

Topological seizure origin detection in electroencephalographic signals. / Wang, Yuan; Ombao, Hernando; Chung, Moo K.
2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015. IEEE Computer Society, 2015. p. 351-354 7163885 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2015-July).

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

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AB - We propose a method for detecting seizure origin in epileptic electroencephalographic (EEG) data based on a novel multi-scale topological technique called persistent homology (PH). Among several PH descriptors, persistence landscape (PL) possesses many desirable properties for rigorous statistical inference. By building PLs on EEG epilepsy signals smoothed by a weighted Fourier series (WFS) expansion, we compared the before and during phases of a seizure attack in a patient diagnosed with left temporal epilepsy and successfully identified site T3 as the origin of the seizure attack.

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T2 - 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015

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ER -

Topological seizure origin detection in electroencephalographic signals

Abstract

Publication series

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Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this