RT Conference Proceedings
T1 Pre-Ictal Phase Detection with SVMs
A1 Ramos-Cózar, Julián
A1 Zeljković, Vesna
A1 González-Linares, José María
A1 Guil-Mata, Nicolás
A1 Bojic, Milena
A1 Valev, Ventzeslav
K1 Epilepsia - Diagnóstico - Aplicaciones informáticas
AB Over 50 million persons worldwide are affected by epilepsy. Epilepsy is a brain disorder known for sudden, unexpected transitions from normal to pathological behavioral states called epileptic seizures. Epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. There is a need for a quick screening process that could help neurologist diagnose and determine the patient’s treatment. Electroencephalogram has been traditionally used to diagnose patients by evaluating those brain functions that may correspond to epilepsy. The objective of this paper is to implement a novel detection technique of pre-ictal state that announces epileptic seizures from the online EEG data analysis. Unlike most published methods, that are aimed to distinguish only the normal from the epilepsy state, in this work the pre-ictal state is introduced as a new patient status, thus differentiating three possible states: normal (healthy), pre-ictal and epileptic seizure. In this manner, the patient should get timely alert about the possible seizure attack so that she/he can stop with its activities and take safety precautions.
YR 2014
FD 2014-07-29
LK http://hdl.handle.net/10630/7950
UL http://hdl.handle.net/10630/7950
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.                    This work is partially supported by the Ministry of Education and Science of Spain under contract TIN2010-16144 and Junta de Andalucía under contract TIC-1692.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026