Recurrence quantification analysis of heart rate variability during continuous incremental exercise test in obese...

Area of Science:

• Exercise Physiology
• Cardiovascular Dynamics
• Nonlinear Time Series Analysis

Background:

• Metabolic changes during incremental exercise are crucial for tailoring exercise programs, especially for obese individuals.
• Traditional methods for identifying aerobic thresholds often require expensive gas exchange analysis.
• Heart rate variability (HRV) analysis offers a non-invasive window into autonomic nervous system function during exercise.

Purpose of the Study:

• To develop and validate a novel method for detecting metabolic thresholds using heart rate variability analysis.
• To assess the feasibility of using recurrence quantification analysis (RQA) of RR interval time series for identifying exercise-induced phase transitions.
• To provide a personalized exercise prescription approach for obese subjects based on individual metabolic responses.

Main Methods:

• Analysis of heart rate variability (HRV) from RR interval time series using recurrence quantification analysis (RQA).
• Identification of phase transitions in cardiac signal dynamics within the RR interval tachogram.
• Comparison of detected phase transitions with aerobic threshold identified via traditional gas exchange measurements (VO2 consumption).

Main Results:

• A distinct transition in cardiac signal dynamics was detected using RQA, correlating perfectly with the aerobic threshold.
• Specific patterns in the recurrence plot of RR intervals were identified as indicators of phase transitions between different dynamic regimes.
• The timing of these phase transitions closely matched changes in VO2 consumption, validating the HRV-based method.

Conclusions:

• Nonlinear analysis of RR interval time series, specifically RQA, can accurately detect metabolic thresholds during incremental exercise.
• This method offers a personalized and accessible approach to exercise prescription, suitable for both clinical settings and low-cost wearable devices.
• The findings highlight the coupling between respiratory and cardiac systems during exercise, detectable through HRV phase transitions.