DocumentCode :
724860
Title :
Topological seizure origin detection in electroencephalographic signals
Author :
Yuan Wang ; Ombao, Hernando ; Chung, Moo K.
Author_Institution :
Dept. of Biostat. & Med. Inf., UW Madison, Madison, WI, USA
fYear :
2015
fDate :
16-19 April 2015
Firstpage :
351
Lastpage :
354
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 :
Fourier series; electroencephalography; medical disorders; medical signal detection; medical signal processing; neurophysiology; statistical analysis; EEG epilepsy signals; PH descriptors; PL possesses; WFS expansion; electroencephalographic signals; epileptic electroencephalographic data; left temporal epilepsy; multiscale topological technique; patient diagnosis; persistence landscape; persistent homology; statistical inference; topological seizure origin detection; weighted Fourier series expansion; Bars; Brain modeling; Computational modeling; Electroencephalography; Epilepsy; Noise; Smoothing methods; EEG; epilepsy; persistence landscape; persistent homology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location :
New York, NY
Type :
conf
DOI :
10.1109/ISBI.2015.7163885
Filename :
7163885
Link To Document :
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