A Page-Hinkley based method for HFOs detection in epileptic depth-EEG

Interictal High Frequency Oscillations, (HFOs [30600 Hz]), recorded from intracerebral electroencephalo-graphy (iEEG) in epileptic brain, showed to be potential biomarkers of epilepsy. Hence, their automatic detection has become a subject of high interest. So far, all detection algorithms consisted...

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Bibliographic Details
Published in2017 25th European Signal Processing Conference (EUSIPCO) pp. 1295 - 1299
Main Authors Jrad, Nisrine, Kachenoura, Amar, Nica, Anca, Merlet, Isabelle, Wendling, Fabrice
Format Conference Proceeding
LanguageEnglish
Published EURASIP 01.08.2017
Subjects
Abrupt change
Cumulative Sum test
epilepsy
Europe
Gabor Transform
Hafnium oxide
interictal High Frequency Oscillations
intracerebral electroencephalo-graphy
Oscillators
Page-Hinkley algorithm
Sensitivity
Signal processing
Signal processing algorithms
Transient analysis
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Summary:Interictal High Frequency Oscillations, (HFOs [30600 Hz]), recorded from intracerebral electroencephalo-graphy (iEEG) in epileptic brain, showed to be potential biomarkers of epilepsy. Hence, their automatic detection has become a subject of high interest. So far, all detection algorithms consisted of comparing HFOs energy, computed in bands of interest, to a threshold. In this paper, a sequential technique was investigated. Detection was based on a variant of the Cumulative Sum (CUSUM) test, the so-called Page-Hinkley algorithm showing optimal results for detecting abrupt changes in the mean of a normal random signal. Experiments on simulated and real datasets showed the good performance of the method in terms of sensitivity and false detection rate. Compared to the classical thresholding, Page-Hinkley showed better performance.
ISSN:2076-1465
DOI:10.23919/EUSIPCO.2017.8081417