Characterization of Dynamic Interactions Between Cardiovascular Signals by Time-Frequency Coherence

Citations Over TimeTop 15% of 2011 papers

Abstract

An assessment of the dynamic interactions between cardiovascular signals can provide valuable information to improve the understanding of cardiovascular control. In this study, two methodologies for the characterization of time-frequency (TF) coherence between cardiovascular signals are described. The methodologies are based on the smoothed pseudo-Wigner-Ville distribution (SPWVD) and multitaper spectrogram (MTSP), and include the automatic assessment of the significance level of coherence estimates. The capability to correctly localize TF regions, where signals are locally coupled, is assessed using computer-generated data, and data from healthy volunteers. The SPWVD allows for the localization of these regions with higher accuracy (AC > 96.9% for SNR ≥ 5 dB) than the MTSP (AC > 84.4% for SNR ≥ 5 dB). In 14 healthy subjects, TF coherence analysis was used to describe the changes, which a tilt table test provokes in the cardiovascular control. Orthostatic stress provoked an increase in the coupling between R-R variability (RRV) and systolic arterial pressure variability; it did not provoke any significant changes in the coupling between RRV and respiration. In HF band, it decreased the strength of the coupling between RRV and pulse interval variability estimated from arterial pressure signal.

Related Papers

• → The multitaper reassigned spectrogram for oscillating transients with Gaussian envelopes(2022)13 cited
• → Signal extraction via multitaper spectra of nonstationary data(2002)8 cited
• → Classification of bird song syllables using singular vectors of the multitaper spectrogram(2015)8 cited
• Time Frequency Spectral Representation of Auditory Brainstem Response (ABR) Data(2012)
• → Automatic Time-Frequency Analysis of Echolocation Signals Using the Matched Gaussian Multitaper Spectrogram(2017)