https://www.hal.inserm.fr/inserm-00130050Senhadji, LotfiLotfiSenhadjiLTSI - Laboratoire Traitement du Signal et de l'Image - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - INSERM - Institut National de la Santé et de la Recherche MédicaleWendling, FabriceFabriceWendlingLTSI - Laboratoire Traitement du Signal et de l'Image - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - INSERM - Institut National de la Santé et de la Recherche MédicaleEpileptic transient detection: wavelets and time-frequency approaches.HAL CCSD2002time-scalewaveletstime-frequencytransient detectionsignature recognitionnon-stationary signalsEEGSEEGepileptic signaltransientepilepsy[SDV.IB] Life Sciences [q-bio]/Bioengineering[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[MATH.MATH-RT] Mathematics [math]/Representation Theory [math.RT][MATH.MATH-ST] Mathematics [math]/Statistics [math.ST][STAT.TH] Statistics [stat]/Statistics Theory [stat.TH][INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSenhadji, Lotfi2007-02-15 09:41:372022-09-02 14:49:022007-02-15 09:41:11enJournal articleshttps://www.hal.inserm.fr/inserm-00130050/document10.1016/S0987-7053(02)00304-0application/pdf1This paper is aimed at presenting the two main classes of nonstationary signal transforms that are currently used to analyze and to characterize EEG observations. Time-scale methods, or wavelet transforms, allow a time versus duration analysis to be performed whereas time-frequency methods allow spectral contents to be analyzed as a function of time. These two types of transform are well suited to the study of changes either localized or progressive that may be observed in EEG signal dynamics and that sign the evolution of underlying physiological mechanisms. The potential interest of these methods in nonstationary signal representation is illustrated through several academic examples. Then, methods are applied on real EEG signals to solve problems such that the detection of interictal transient signals (like spikes or spike-waves) and the recognition of signatures during ictal periods.