Epileptic seizure detection from ECoG using recurrence time statistics

被引：0

作者：

Liu, H ^{[1
]}

Gao, JB ^{[1
]}

Hild, KE ^{[1
]}

Príncipe, JC ^{[1
]}

Sackellares, JC ^{[1
]}

机构：

[1] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA

来源：

PROCEEDINGS OF THE 26TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2004年 / 26卷

关键词：

electrocorticography (ECoG); recurrence time statistics; epilepsy; seizure detection; receiver operating curve;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A recurrence time statistics T1 is defined and used as a feature extraction method for seizure detection. The preliminary data shows that during seizure T1 generates a peak and this peak clearly distinguishes the seizure state from background activity. When applied to multi-channel ECoG recordings, the spatial-temporal signature of T1 can be clearly observed to discriminate seizures. The T1 feature was used for automated seizure detection on two sets of long. term monitoring ECoG data. The detection probability reached 97% with a 0.29 per hour average false alarm rate.

引用

页码：29 / 32

页数：4

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