%0 Conference Proceedings %T A page-hinkley based method for HFOs detection in epileptic depth-EEG %+ Laboratoire Traitement du Signal et de l'Image (LTSI) %A Jrad, N. %A Kachenoura, A. %A Nica, A. %A Merlet, I. %A Wendling, F. %Z ANR-13-TECS-0013, ANR, Agence Nationale de la Recherche %< avec comité de lecture %B 25th European Signal Processing Conference, EUSIPCO 2017 %C Kos, Greece %I Institute of Electrical and Electronics Engineers Inc. %V 2017-January %P 1295-1299 %8 2017-08-28 %D 2017 %R 10.23919/EUSIPCO.2017.8081417 %K Abrupt change %K Cumulative Sum test %K Epilepsy %K Gabor Transform %K Interictal High Frequency Oscillations %K Intracerebral electroencephalo-graphy %K Page-Hinkley algorithm %Z Life Sciences [q-bio]/BioengineeringConference papers %X Interictal High Frequency Oscillations, (HFOs [30-600 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. %G English %L hal-01740209 %U https://univ-rennes.hal.science/hal-01740209 %~ UNIV-RENNES1 %~ LTSI %~ STATS-UR1 %~ UR1-HAL %~ UR1-MATH-STIC %~ TEST-UR-CSS %~ UNIV-RENNES %~ ANR %~ UR1-MATH-NUM %~ UR1-BIO-SA