An Algorithm For Detecting Seizure Termination in Scalp EEG

被引：0

作者：

Shoeb, Ali ^{[1
]}

Kharbouch, Alaa ^{[1
]}

Soegaard, Jacqueline ^{[1
]}

Schachter, Steven ^{[1
]}

Guttag, John ^{[1
]}

机构：

[1] Massachusetts Gen Hosp, Boston, MA 02114 USA

来源：

2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2011年

关键词：

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Little effort has been devoted to developing algorithms that can detect the cessation of seizure activity in scalp EEG. Such algorithms could facilitate clinical applications such as the estimation of seizure duration or the delivery of therapies designed to mitigate postictal period symptoms. In this paper, we present a method for detecting the termination of seizure activity. When tested on 133 seizures from a public database, our method detected the end of 132 seizures with a mean absolute error of 10.3 +/- 5.5 seconds of the time marked by an electroencephalographer. Furthermore, by pairing our seizure end detector with a previously published seizure onset detector, we could automatically estimate the duration of 85% of test seizures within a 15 second error margin.

引用

页码：1443 / 1446

页数：4

共 7 条

[1]

FRANC V, 2001, COMPUTER VISION COMP, P143

[2]

Gangadhar B., 1995, IEEE ENG MED BIOL SO, P337

[3] Detecting epileptic seizures in long-term human EEG: A new approach to automatic online and real-time detection and classification of polymorphic seizure patterns [J].