179 406

Cited 4 times in

Automatic Identification of Interictal Epileptiform Discharges in Secondary Generalized Epilepsy

Authors
 Won-Du Chang  ;  Ho-Seung Cha  ;  Chany Lee  ;  Hoon-Chul Kang  ;  Chang-Hwan Im 
Citation
 COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, Vol.2016 : 8701973, 2016 
Journal Title
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
ISSN
 1748-670X 
Issue Date
2016
Abstract
Ictal epileptiform discharges (EDs) are characteristic signal patterns of scalp electroencephalogram (EEG) or intracranial EEG (iEEG) recorded from patients with epilepsy, which assist with the diagnosis and characterization of various types of epilepsy. The EEG signal, however, is often recorded from patients with epilepsy for a long period of time, and thus detection and identification of EDs have been a burden on medical doctors. This paper proposes a new method for automatic identification of two types of EDs, repeated sharp-waves (sharps), and runs of sharp-and-slow-waves (SSWs), which helps to pinpoint epileptogenic foci in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). In the experiments with iEEG data acquired from a patient with LGS, our proposed method detected EDs with an accuracy of 93.76% and classified three different signal patterns with a mean classification accuracy of 87.69%, which was significantly higher than that of a conventional wavelet-based method. Our study shows that it is possible to successfully detect and discriminate sharps and SSWs from background EEG activity using our proposed method.
Files in This Item:
T201605847.pdf Download
DOI
10.1155/2016/8701973
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pediatrics (소아과학교실) > 1. Journal Papers
Yonsei Authors
Kang, Hoon Chul(강훈철) ORCID logo https://orcid.org/0000-0002-3659-8847
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/153040
사서에게 알리기
  feedback

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse

Links