Principal Component Analysis in ECG Signal Processing

被引：0

作者：

Francisco Castells

Pablo Laguna

Leif Sörnmo

Andreas Bollmann

José Millet Roig

机构：

[1] Universidad Politécnica de Valencia (UPV),Grupo de Investigación en Bioingenería, Electrónica y Telemedicina, Departamento de Ingenería Electrónica, Escuela Politécnica Superior de Gandía

[2] Ctra. Nazaret-Oliva,Communications Technology Group, Aragón Institute of Engineering Research

[3] University of Zaragoza,Signal Processing Group, Department of Electrical Engineering

[4] Lund University,Department of Cardiology

[5] Otto-von-Guericke-University Magdeburg,Grupo de Investigación en Bioingenería, Electrónica y Telemedicina, Departamento de Ingenería Electrónica

[6] Universidad Politécnica de Valencia,undefined

来源：

EURASIP Journal on Advances in Signal Processing | / 2007卷

关键词：

Ischemia; Principal Component Analysis; Atrial Fibrillation; Myocardial Ischemia; Quantum Information;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loève transform is explained. Aspects on PCA related to data with temporal and spatial correlations are considered as adaptive estimation of principal components is. Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrial fibrillation, and analysis of body surface potential maps.

引用

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