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