Times Varying Spectral Coherence Investigation of Cardiovascular Signals Based on Energy Concentration in Healthy Young and Elderly Subjects by the Adaptive Continuous Morlet Wavelet Transform

Abstract

ObjectiveThe aims of this study, to investigate the interaction among heart rate variability (HRV), respiratory, systolic arterial blood pressure variability (SABPV) and systolic arterial pressure interval variability (APIV) signals for understanding of cardiovascular control. MethodsIn this study, three methods referred as adaptive continuous Morlet wavelet transform (ADCMWT), adaptive Stockwell transform (ADST) and adaptive modified Stockwell transform (ADMST) was used to assess the accuracy (AC) of time-varying spectral coherence (TVSC). The adaptation of these estimators was based on maximum energy concentration measurement. The capability to correct temporal localization of time–frequency regions was validated on synthetic time series data modeled as dynamic characteristics of cardiovascular signals. ResultsThe results on synthetic simulated data show that the ADCMWT method allows for the temporal localization of the time–frequency regions with higher accuracy (AC > 96.074% for SNR ≥ 0 dB), compared to ADST (AC > 90.71% for SNR ≥ 0 dB) and ADMST (AC > 84.45% for SNR ≥ 5 dB). Further, the ADCMWT was applied to real cardiovascular data obtained from Fantasia standard data base and grouped as, 8 young subjects (4M + 4F, age range 23–32) and 8 elderly subjects (4M + 4F, age range 70–82) for estimating the TVSC in low frequency (LF) band (0.04 Hz–0.15 Hz) and high frequency (HF) band (0.15 Hz–0.4 Hz) of HRV spectrum. The global result depict that the median value of interquartile range of coherency between HRV-SABPV and HRV-APIV signals in LF and HF band were significantly (p=0.00001) lower in elderly group subjects compared to young group subjects. The coupling between HRV-Respiratory signals in LF band was not significantly affected with the aging of healthy subjects. However, this coupling in HF band significantly reduced in elderly compare to young group subjects (p=0.0125). ConclusionThe comparative study shows that the time-varying spectra and accurate localization of coupling between two physiological signals can be affected by energy concentration. The ADCMWT at w0=6, could be an alternative, possibly more suitable and highly accurate method for assessment and detection of time varying spectral and coherence components of cardiovascular time series.