A Semi-Automated Method for Epileptiform Transient Detection in the EEG of the Fetal Sheep Using Time-Frequency Analysis

被引：7

作者：

Walbran, Anita C. ^{[1
]}

Unsworth, Charles P. ^{[1
]}

Gunn, Alistair J. ^{[2
]}

Bennet, Laura ^{[2
]}

机构：

[1] Univ Auckland, Dept Engn Sci, Auckland 1010, New Zealand

[2] Univ Auckland, Fac Med & Hlth Sci, Dept Physiol, Auckland 92019, New Zealand

来源：

2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20 | 2009年

关键词：

AUTOMATIC DETECTION; HYPOTHERMIA; MULTISTAGE; EVENTS;

D O I：

10.1109/IEMBS.2009.5332431

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Perinatal hypoxia remains a significant cause of brain damage. Currently there are no biomarkers to detect the at risk brain. Recent research, however, suggests that the appearance of epileptiform transients in the first 6-8 hours after hypoxia (the latent phase of injury) are predictive of neural outcome. To quantify this further a key need is to automate EEG signal analysis to aid clinical staff with the vast amounts of complex data to review. In this study, we present a semi-automated method for spike detection in the fetal sheep EEG. The method utilizes the short time Fourier transform and peak separation to extract spikes. The performance of the method was found to be high in sensitivity and selectivity over 3 distinct time points.

引用

页码：17 / +

页数：2

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