Prediction of seizure onset zone in epilepsy patients via a network coupling measure
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- dc.contributor.author Elizondo Urrutia, Saioa
- dc.date.accessioned 2025-02-13T10:26:08Z
- dc.date.available 2025-02-13T10:26:08Z
- dc.date.issued 2024
- dc.description Treball de Fi de Grau en Enginyeria Biomèdica. Curs 2023-2024
- dc.description Tutor: Marc Grau Leguiaca
- dc.description.abstract Epilepsy, a chronic neurological disorder characterized by recurrent seizures, affects millions globally. For patients with drug-resistant epilepsy, surgical intervention becomes a viable option. However, precise localization of the seizure onset zone (SOZ) is crucial for successful surgery. This thesis investigates the potential of the L measure, a non-linear method analyzing directional couplings between brain regions, for SOZ detection in pharmacoresistant epilepsy patients using electroencephalography (EEG) data recorded in a natural environment. We analyzed seizure dynamics in 10 patients using EEG data from the Melbourne NeuroVista Seizure Prediction Trial database. Applying the L measure, we explored connectivity patterns within and across brain regions during pre-ictal, seizure onset, and ictal stages. Network analysis using graph theory metrics assessed these variations across EEG channels and patients to identify potential SOZ locations. Furthermore, we developed a novel method, to track channel connectivity dynamics during seizures, potentially detecting the SOZ with higher temporal resolution. These findings are expected to contribute to a more comprehensive understanding of seizure dynamics and the potential of the L measure for SOZ detection in pharmacoresistant epilepsy patients. This research may pave the way for improved surgical planning and treatment outcomes for this challenging patient population.en
- dc.identifier.uri http://hdl.handle.net/10230/69600
- dc.language.iso eng
- dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0
- dc.subject.keyword Epilepsyen
- dc.subject.keyword Seizureen
- dc.subject.keyword EEGen
- dc.subject.keyword Seizure onset zoneen
- dc.subject.keyword L measureen
- dc.subject.keyword Directional couplingen
- dc.subject.keyword Network analysisen
- dc.subject.keyword Graph theoryen
- dc.subject.other Treball de fi de grau – Curs 2023-2024
- dc.title Prediction of seizure onset zone in epilepsy patients via a network coupling measure
- dc.type info:eu-repo/semantics/bachelorThesis