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A Multi-Channel Approach for Cortical Stimulation Artefact Suppression in Depth EEG Signals Using Time-Frequency and Spatial Filtering

Authors :
Ram Bilas Pachori
Louis Maillard
Valérie Louis-Dorr
Steven Le Cam
Radu Ranta
Abhijit Bhattacharyya
Louise Tyvaert
Sophie Colnat-Coulbois
Indian Institute of Technology Indore (IITI)
Centre de Recherche en Automatique de Nancy (CRAN)
Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Service de neurologie [CHRU Nancy]
Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)
Service de Neurochirurgie [CHRU Nancy]
Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)
Source :
IEEE Transactions on Biomedical Engineering, IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2019, 66 (7), pp.1915-1926. ⟨10.1109/TBME.2018.2881051⟩
Publication Year :
2019
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2019.

Abstract

International audience; Objective: The stereo electroencephalogram (SEEG) recordings are the sate of the art tool used in pre-surgical evaluation of drug-unresponsive epileptic patients. Coupled with SEEG, electrical cortical stimulation (CS) offer a complementary tool to investigate the lesioned/healthy brain regions and to identify the epileptic zones with precision. However, the propagation of this stimulation inside the brain masks the cerebral activity recorded by nearby multi-contact SEEG electrodes. The objective of this paper is to propose a novel filtering approach for suppressing the CS artifact in SEEG signals using time, frequency as well as spatial information.Methods: The method combines spatial filtering with tunable-Q wavelet transform (TQWT). SEEG signals are spatially filtered to isolate the CS artifacts within a few number of sources/components. The artifacted components are then decomposed into oscillatory background and sharp varying transient signals using tunable-Q wavelet transform (TQWT). The CS artifact is assumed to lie in the transient part of the signal. Using prior known time-frequency information of the CS artifacts, we selectively mask the wavelet coefficients of the transient signal and extract out any remaining significant electro-physiological activity.Results: We have applied our proposed method of CS artifact suppression on simulated and real SEEG signals with convincing performance. The experimental A. Bhattacharyya 2 results indicate the effectiveness of the proposed approach.Conclusion: The proposed method suppresses CS artifacts without affecting the background SEEG signal. Significance: The proposed method can be applied for suppressing both low and high frequency CS artifacts and outperforms current methods from the literature. Index Terms cortical stimulation, SEEG, tunable-Q wavelet transform, subspace correlation approach, blind source separation.

Details

ISSN :
15582531 and 00189294
Volume :
66
Database :
OpenAIRE
Journal :
IEEE Transactions on Biomedical Engineering
Accession number :
edsair.doi.dedup.....12da22ba8d1943f9e1fee35cc789f062
Full Text :
https://doi.org/10.1109/tbme.2018.2881051