Seizure Onset Localization in Focal Epilepsy using intracranial-EEG data and the Schrodinger Operator's Spectrum

Maria Sara Nour Sadoun*, Taous Meriem Laleg-Kirati

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures that vary from short attention failure to convulsions. Despite its threats and limitations, existing medications target only specific types of seizures while up to 33% of epileptic conditions are drug-resistant. The best available treatment is surgical resection or neurostimulation and both require accurate localization of the Seizure Onset Zone. Its delineation is performed by analyzing neuronal activity by epileptologists, however, it is time-consuming and error-prone. Therefore, if the said zone could be located faster and more accurately, the seizure freedom of patients would be significantly enhanced. An effort within the field is aiming at developing computer-aided methods to assist medical experts and this starts with characterizing electrical neural activity. In the present paper, a new method for characterizing the epileptic intracranial EEG is proposed. The method is based on a semi-classical signal analysis (SCSA) method. Functional connectivity measures are used to compare patterns observed when feeding these measures with the raw time-series and when feeding them with SCSA features. The obtained results are undeniably promising for further investigation and improvement of the framework.Clinical relevance - The paper contributes to the design methods and algorithms to build reliable software solutions to assist medical experts in identifying Seizure Onset Zone in focal epilepsy.

Original languageEnglish (US)
Title of host publication2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350324471
DOIs
StatePublished - 2023
Event45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Sydney, Australia
Duration: Jul 24 2023Jul 27 2023

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023
Country/TerritoryAustralia
CitySydney
Period07/24/2307/27/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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