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Medical & Biological Engineering & Computing

Erschienen in:

01.06.2006 | Original Article

Noise reduction in magnetocardiography by singular value decomposition and independent component analysis

verfasst von: D. DiPietroPaolo, H.-P. Müller, G. Nolte, S. N. Erné

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 6/2006

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Abstract

In the routine recording of magnetocardiograms (MCGs), it is necessary to underline the problem of noise cancellation. Source separation has often been suggested to solve this problem. In this paper, blind source separation (BSS), by means of singular value decomposition (SVD) and independent component analysis (ICA), was used for noise reduction in MCG data to improve the signal to noise ratio. Special techniques, based on statistical parameters, for identifying noise and disturbances, have been introduced to automatically eliminate noise-related and disturbance-related components before reconstructing cleaned data sets. The results show that ICA and SVD can detect and remove a variety of noise and artefact sources from MCG data, as well as from stress MCG.

Vorheriger Artikel Inertial measurements of upper limb motion

Nächster Artikel Non-invasive continuous estimation of blood flow changes in human patellar bone

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Titel: Noise reduction in magnetocardiography by singular value decomposition and independent component analysis
verfasst von: D. DiPietroPaolo
H.-P. Müller
G. Nolte
S. N. Erné
Publikationsdatum: 01.06.2006
Verlag: Springer-Verlag
Erschienen in: Medical & Biological Engineering & Computing / Ausgabe 6/2006
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-006-0055-z

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