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Related Experiment Video

Updated: May 25, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

Time-frequency phase differences and phase locking to characterize dynamic interactions between cardiovascular

Michele Orini¹, Raquel Bailón, Luca T Mainardi

¹GTC, I3A, IIS Aragón, Universidad de Zaragoza and with CIBER–BBN, Zaragoza, Spain. michele@unizar.es

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 19, 2012

Summary

This summary is machine-generated.

This study introduces a novel cross time-frequency analysis to precisely measure cardiovascular signal synchronization. The method accurately estimates phase differences and phase locking, crucial for understanding cardiovascular interactions.

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Area of Science:

Cardiovascular Physiology
Signal Processing
Biomedical Engineering

Background:

Cardiovascular signal analysis often requires precise estimation of synchronization.
Existing methods for phase difference and phase locking estimation have limitations.

Purpose of the Study:

To develop and validate a novel cross time-frequency (TF) analysis for estimating phase differences and phase locking between cardiovascular signals.
To assess the performance of the proposed methodology in simulations and a real-world physiological test.

Main Methods:

Cross time-frequency analysis utilizing the smoothed pseudo Wigner-Ville distribution.
Coherence analysis to measure the degree of similarity in synchronization changes.
Simulation studies using R-R variability (RRV) signals.
Comparative analysis against an instantaneous frequency-based estimator.
Application to RRV and systolic arterial pressure variability during tilt table testing.

Main Results:

The methodology provided accurate phase difference estimates in simulations, with low error even at low signal-to-noise ratios (SNR).
The proposed estimator outperformed a previously established method.
Head-up tilt induced significant changes in phase differences (time delay) in the high-frequency (HF) range.
Phase locking decreased upon head-up tilt but recovered within approximately 2 minutes.

Conclusions:

The developed cross time-frequency analysis is a robust and accurate tool for quantifying cardiovascular signal synchronization.
This method offers improved performance over existing techniques for analyzing cardiovascular interactions.
The findings provide insights into the dynamic changes in cardiovascular regulation during postural challenges.