In this paper a novel method, called WICA, based on the joint use of wavelet transform (WT) and independent component analysis (ICA) is discussed. The main advantage of this method is that it encompasses the characteristics of WT and ICA. In order to show the novelty of our method, we present a biomedical signal processing application in which ICA has poor performances, whereas WICA yields good results. In particular, we discuss the artifact cancellation in electrocardiographic (ECG) signals. The results show the ability of WICA to cancel some artifact from ECG when only two signals are recorded.
Artifact Cancellation from Electrocardiogram by Mixed Wavelet-ICA Filter / LA FORESTA, F.; Mammone, N.; Morabito, C.. - 3931:(2006), pp. 78-82. (Intervento presentato al convegno WIRN 2005 tenutosi a Vietri S. M. (SA), Italy nel June 8-11) [10.1007/11731177_12].
Artifact Cancellation from Electrocardiogram by Mixed Wavelet-ICA Filter
F. LA FORESTA;N. MAMMONE;C. MORABITO
2006-01-01
Abstract
In this paper a novel method, called WICA, based on the joint use of wavelet transform (WT) and independent component analysis (ICA) is discussed. The main advantage of this method is that it encompasses the characteristics of WT and ICA. In order to show the novelty of our method, we present a biomedical signal processing application in which ICA has poor performances, whereas WICA yields good results. In particular, we discuss the artifact cancellation in electrocardiographic (ECG) signals. The results show the ability of WICA to cancel some artifact from ECG when only two signals are recorded.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
