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Analyse automatique des crises d'épilepsie du lobe temporal à partir des EEG de surface

Abstract : The objective of this work was the development of a temporal lobe epilepsy seizures characterization methodology. The characterization was realized through scalp EEG analysis.
Recent researches, mainly pursued on signal recorded on depth electrodes, showed an evolution of the synchronizations between cerebral structures, allowing a characterization of the temporal lobe seizures dynamic.
The originality of our work consisted in the extension of the methods developed on depth electrodes to the study of scalp EEGs. From the medical point of view, this work lied within the scope of the presurgical diagnosis assistance.
Methods of relation measurement, such as coherence, Directed Transfer Function (DTF), linear (r²) or non-linear correlation (h²), were adapted to answer these problems. Various criteria, defined from clinical indications, allowed the description of the advantages of the non-linear correlation coefficient in the study of epileptic seizures from scalp EEGs.
The characterization of the evolution of the non-linear correlation coefficient was used as the base of the development of three signal processing applications:
- The first was the determination of the side Epileptic Zone (EZ) at the onset of a seizure.
- The search for an epileptic pattern constituted the second application. The pattern was extracted by an algorithm that was looking for the similarities between two seizures.
- A classification of the temporal lobe seizures constituted the third application. It was carried out by extracting a set of characteristics from the patterns extracted by the algorithm of second stage.
The large data base, which contained eighty seven seizures recorded on forty-three patients (two crises per patient, three for one of them), guaranteed a statistical significativity.
Concerning the results, a rate of good lateralization of about 88% was obtained. This result was very interesting, as in the literature it was some times reached, but only by exploiting a multimodal data set or with non-automatics methods. The classification gave a sensitivity of 85% for the medial seizures and 58% for the mésio-lateral ones.
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Submitted on : Friday, December 8, 2006 - 1:41:39 PM
Last modification on : Friday, October 23, 2020 - 4:36:18 PM
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Matthieu Caparos. Analyse automatique des crises d'épilepsie du lobe temporal à partir des EEG de surface. Traitement du signal et de l'image [eess.SP]. Institut National Polytechnique de Lorraine - INPL, 2006. Français. ⟨tel-00118993⟩

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