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.
journal_name
Med Biol Eng Computjournal_title
Medical & biological engineering & computingauthors
DiPietroPaolo D,Müller HP,Nolte G,Erné SNdoi
10.1007/s11517-006-0055-zsubject
Has Abstractpub_date
2006-06-01 00:00:00pages
489-99issue
6eissn
0140-0118issn
1741-0444journal_volume
44pub_type
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