Time-Frequency Analysis of Cardiovascular Variability during an Orthostatic Stress by Complete EMD.

Area of Science:

• Cardiovascular physiology
• Nonlinear signal analysis
• Autonomic nervous system research

Background:

• The autonomic nervous system (ANS) regulates cardiovascular responses to stressors.
• Traditional analysis methods struggle with nonstationary cardiovascular signals.
• Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) offers a novel approach for nonlinear, time-variant signal analysis.

Purpose of the Study:

• To investigate autonomic nervous system regulation in health and orthostatic intolerance using CEEMDAN.
• To analyze cardiovascular variability signals during a head-up tilt test (HUTT).
• To establish a reference for diagnosing orthostatic intolerance (OI).

Main Methods:

• Analysis of beat-to-beat intervals (BBI) and systolic blood pressure (SYS) variability using CEEMDAN.
• Application of the head-up tilt test (HUTT) in healthy females and female patients with OI.
• Investigation of instantaneous amplitudes and frequencies of intrinsic mode functions (IMFs).

Main Results:

• Statistical differences were observed in the high-frequency band of BBI between groups.
• Greater differences were found in the high and low-frequency bands of SYS during the HUTT transition.
• The average Hilbert-Huang Spectrum (HHS) of healthy subjects during HUTT was identified.

Conclusions:

• CEEMDAN effectively analyzes cardiovascular variability signals for insights into ANS regulation.
• Distinct patterns in BBI and SYS variability emerge during HUTT in healthy versus OI individuals.
• The reference HHS for healthy subjects can aid in diagnosing OI by detecting deviations in cardiovascular signal patterns.