Quantifying cardio-pulmonary correlations using the cross-wavelet transform: validating a correlative method.

Dynamic changes in physiologic systems have become an increasingly important topic in biomedical signal processing. To demonstrate a novel approach to this type of analysis, we recorded the cardiac and respiratory rhythms of six normal subjects over 5 minutes. We used cross-wavelet transforms to identify any correlations between these signals and then a unique approach to surrogate data generation in the frequency domain to confirm the statistical significance of the correlations that were found.