Literature DB >> 17313329

The role of independent component analysis in the signal processing of ECG recordings.

Francisco Castells1, Antonio Cebrián, José Millet.   

Abstract

Independent component analysis (ICA) is an emerging technique for multidimensional signal processing. In recent years, these techniques have been proposed for solving a large number of biomedical applications. This work reviews current knowledge on ICA in electrocardiographic (ECG) analysis. The benefits that ICA can bring to clinical practice are illustrated with four relevant clinical applications: foetal ECG extraction from maternal ECG recordings, analysis of atrial fibrillation, ECG denoising and removal of pacemaker artefacts.

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Year:  2007        PMID: 17313329     DOI: 10.1515/BMT.2007.005

Source DB:  PubMed          Journal:  Biomed Tech (Berl)        ISSN: 0013-5585            Impact factor:   1.411


  2 in total

1.  Independent component analysis and decision trees for ECG holter recording de-noising.

Authors:  Jakub Kuzilek; Vaclav Kremen; Filip Soucek; Lenka Lhotska
Journal:  PLoS One       Date:  2014-06-06       Impact factor: 3.240

2.  Improved detection of paroxysmal atrial fibrillation utilizing a software-assisted electrocardiogram approach.

Authors:  Jürgen R Schaefer; Dieter Leussler; Ludger Rosin; David Pittrow; Thomas Hepp
Journal:  PLoS One       Date:  2014-02-28       Impact factor: 3.240

  2 in total

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