On the use of wavelets to separate dynamical activities embedded in a time series

In this work a first attempt is made to separate dynamical activity in signals by decomposing frequency sub-bands of the original observable signal. The authors use multiresolution wavelets to decompose electrocardiogram (ECG) signals into several frequency sub-bands and calculated the correlation dimension to determine the presence or absence of low-dimensional dynamics. Although the results must be considered as very preliminary, some evidence is presented to show that a low dimensional activity precedes the actual incidence of the tachyarrhythmia. The authors hypothesize the signal decomposition by wavelet analysis may enhance the ability to locate low dimensional activity in cardiac arrhythmias.