2026-04-17T19:07:36Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/696002025-12-19T20:25:58Zcom_2072_6col_2072_452954

00925njm 22002777a 4500 dc Elizondo Urrutia, Saioa author 2025-02-13T10:26:08Z 2025-02-13T10:26:08Z 2024 Treball de Fi de Grau en Enginyeria Biomèdica. Curs 2023-2024 Tutor: Marc Grau Leguia 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. Treball de fi de grau – Curs 2023-2024 Epilepsy Seizure EEG Seizure onset zone L measure Directional coupling Network analysis Graph theory Prediction of seizure onset zone in epilepsy patients via a network coupling measure