Can EEG processing reveal seizure prediction patterns?

被引：0

作者：

Tito, Maria T. ^{[1
]}

Ayala, Melvin ^{[1
]}

Yaylali, Ilker ^{[1
]}

Cabrerizo, Mercedes ^{[1
]}

Barreto, Armando ^{[1
]}

Rishe, Naphtali ^{[1
]}

Adjouadi, Malek ^{[1
]}

机构：

[1] Florida Int Univ, Dept Elect & Comp Engn, 10555 W Fragler St, Miami, FL 33174 USA

来源：

PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON GRAPHICS AND VISUALIZATION IN ENGINEERING | 2007年

基金：

美国国家科学基金会;

关键词：

EEG; epilepsy; seizure prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Epilepsy is characterized by an unexpected and frequent malfunction of the brain. Electrical activity in the brain has been studied for years in an attempt to predict seizures. This paper processes raw intracranial EEG recordings from different subjects in the time prior to seizure. A set of indicators is extracted from non-overlapping scrolling windows of I sec duration. The objective was to identify patterns that reveal that a seizure is developing before it occurs. While the exhaustive analysis did not detect patterns appropriate to predict a seizure, some indicators were observed to behave in time more similar independent of the subject. Similar time evolution was found for the activity and the power of the alpha and delta bands. It is also shown that the behavior of the correlation integral is somehow similar minutes before the seizure.

引用

页码：47 / +

页数：3

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