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Communication Dans Un Congrès Année : 2021

Frequency-domain identification of stereoelectroencephalographic transfer functions for brain tissue classification

Résumé

In drug-resistant epileptic patients, direct electrical brain stimulation sessions may be needed to identify epileptic regions on the brain before surgery. In this context, the classification of the brain tissue in which the electrodes are implanted in is very important for the interpretation of observed responses. This paper presents a new method for tissue classification based on the study of the baseline data with signal processing methods and features estimated from non parametric frequency identification of transfer functions. The method is tested on actual data and compared to visual classification of contacts co-registered on magnetic resonance imaging. The results show that good separability between matters, with up to 80% accuracy, can be achieved when considering the pairing of two consecutive electrodes.

Dates et versions

hal-03432818 , version 1 (17-11-2021)

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Citer

Mariana Mulinari Pinheiro Machado, Alina Voda, Gildas Besancon, Guillaume Jean-Paul Claude Becq, Olivier David. Frequency-domain identification of stereoelectroencephalographic transfer functions for brain tissue classification. SYSID 2021 - 19th IFAC Symposium on System Identification (SYSID 2021), Jul 2021, Padoue (virtual), Italy. pp.565-570, ⟨10.1016/j.ifacol.2021.08.420⟩. ⟨hal-03432818⟩
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