Principal component analysis in ECG signal processing

Authors:
Francisco Castells;Pablo Laguna;Leif Sörnmo;Andreas Bollmann;José Millet Roig
Affiliations:
Grupo de Investigación en Bioingenería, Electrónica y Telemedicina, Departamento de Ingenería Electrónica, Escuela Politécnica Superior de Gandía, Universidad Po ...;Communications Technology Group, Aragón Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain;Signal Processing Group, Department of Electrical Engineering, Lund University, Lund, Sweden;Department of Cardiology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany;Grupo de Investigación en Bioingenería, Electrónica y Telemedicina, Departamento de Ingenería Electrónica, Universidad Politécnica de Valencia, Valencia, Spain
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2007

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Abstract

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.