Wavelet Transform and Cross-Correlation as Tools for Seizure Prediction

被引：0

作者：

Botero Suarez, Claudia C. ^{[1
]}

Fonoff, Erich Talamoni ^{[2
]}

Munoz G, Mario Alonso

Godoi, Antonio Carlos ^{[1
]}

Ballester, Gerson ^{[2
]}

Ramirez-Fernandez, Francisco Javier ^{[1
]}

机构：

[1] Univ Sao Paulo, Escola Politecnia, Lab Microeletron, BR-05508 Sao Paulo, Brazil

[2] Univ Sao Paulo, Lab Neurocirurgia Func, BR-05508 Sao Paulo, Brazil

来源：

2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2010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：

This paper describes the detection of preictal bursting using wavelet transform application and cross-correlation analysis. The wavelet transform is applied to data reduction and signal pre-processing. The extracted features provide simplified signals to process by means of the cross-correlation technique. The algorithm has been tested with a set of preictal data, interictal data and spontaneous crises, to determinate its sensitivity and its specificity (False Prediction Rate). The seizure occurrence period and the seizure prediction horizon are also calculated. The algorithm's merits are: 1) high sensitivity and 2) easy implementation.

引用

页码：4020 / 4023

页数：4

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