2026-05-31T02:36:58Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/79502026-02-03T12:29:16Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Ramos-Cózar, Julián
author
Zeljković, Vesna
author
González-Linares, José María
author
Guil-Mata, Nicolás
author
Bojic, Milena
author
Valev, Ventzeslav
2014-07-29T11:17:05Z
2014-07-29T11:17:05Z
2014-07-29
http://hdl.handle.net/10630/7950
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.
eng
Epilepsia - Diagnóstico - Aplicaciones informáticas
Pre-Ictal Phase Detection with SVMs
conference output
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URL
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application/pdf
HPCS 2014a_Riuma.pdf
URL
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HPCS 2014a_Riuma.pdf.txt