Automatic detection of epileptic seizures in long-term EEG records

被引:27
|
作者
Garces Correa, Agustina [1 ]
Orosco, Lorena [1 ]
Diez, Pablo [1 ]
Laciar, Eric [1 ]
机构
[1] Univ Nacl San Juan, Fac Ingn, San Juan, Argentina
关键词
Epilepsy; Intracranial EEG records (iEEG); Power spectrum; EEG frequency bands; Wavelet decomposition; FEATURE-EXTRACTION; ONSET DETECTION; CLASSIFICATION; SYSTEM;
D O I
10.1016/j.compbiomed.2014.11.013
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Epilepsy is a neurological disorder which affects nearly 1.5% of the world's total population. Trained physicians and neurologists visually scan the long-term electroencephalographic (EEG) records to identify epileptic seizures. It generally requires many hours to interpret the data. Therefore, tools for quick detection of seizures in long-term EEG records are very useful. This study proposes an algorithm to help detect seizures in long-term iEEG based on low computational costs methods using Spectral Power and Wavelet analysis. The detector was tested on 21 invasive intracranial EEG (iEEG) records. A sensitivity of 85.39% was achieved. The results indicate that the proposed method detects epileptic seizures in long-term iEEG records successfully. Moreover, the algorithm does not require long processing time due to its simplicity. This feature will allow significant time reduction of the visual inspection of iEEG records performed by the specialists. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:66 / 73
页数:8
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