Principal component analysis in ECG signal processing

Francisco Castells, Pablo Laguna, Leif Sörnmo, Andreas Bollmann, Jose Millet Roig

Research output: Contribution to journalArticlepeer-review

272 Citations (SciVal)

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-Loeve 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.
Original languageEnglish
Pages (from-to)74580
JournalEurasip Journal on Applied Signal Processing
DOIs
Publication statusPublished - 2007

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering

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