Quantifying Stress and Relaxation: A New Measure of Heart Rate Variability as a Reliable Biomarker

Area of Science:

• Physiology
• Psychophysiology
• Biomedical Engineering

Background:

• Current physiological stress response characterization lacks a standard, objective method.
• Existing methods are often subjective (psychological measures) or invasive (blood tests for cortisol).
• Heart rate variability (HRV) is a promising, non-invasive indicator of stress, but conventional metrics have limitations.

Purpose of the Study:

• To introduce and evaluate a novel HRV parameter: normalized variability derived from an RMSSD "Master Curve".
• To compare the efficacy of normalized variability against conventional HRV metrics in characterizing stress and relaxation.

Main Methods:

• Study 1: Induced relaxation using HRV biofeedback or habitual relaxation (N=42).
• Study 2: Induced stress using the Socially Evaluated Cold Pressor Test and Stroop Test (N=9).
• Statistical analysis using the Kolmogorov-Smirnov test to compare HRV metrics (mean HR, log(RMSSD), log(SDNN), normalized variability) before, during, and after interventions.

Main Results:

• Normalized variability demonstrated significant changes during both relaxation and stress (Socially Evaluated Cold Pressor Test).
• Conventional HRV metrics (log(RMSSD), log(SDNN)) did not show significant changes.
• The novel normalized variability parameter proved sensitive to physiological state changes.

Conclusions:

• Normalized variability is a sensitive and objective indicator for characterizing the physiological stress response.
• This novel metric can aid in understanding the complex processes of the autonomic nervous system.
• The proposed normalized variability offers a superior alternative to conventional HRV metrics for stress assessment.