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

Background/Objectives: For the rapid, objective characterization of the physiological stress response, there is currently no generally recognized standard. The stress measurement methods used in practice (e.g., for psychological measures of stress) are often subjective, or in the case of biological...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Rudics Emese
Búzás András
Pálfi Antónia
Szabó Zoltán
Nagy Ádám
Hompoth Emőke Adrienn
Dombi József
Bilicki Vilmos
Szendi István
Dér András
Dokumentumtípus: Cikk
Megjelent: 2025
Sorozat:BIOMEDICINES 13 No. 1
Tárgyszavak:
doi:10.3390/biomedicines13010081

mtmt:35657150
Online Access:http://publicatio.bibl.u-szeged.hu/36270
Leíró adatok
Tartalmi kivonat:Background/Objectives: For the rapid, objective characterization of the physiological stress response, there is currently no generally recognized standard. The stress measurement methods used in practice (e.g., for psychological measures of stress) are often subjective, or in the case of biological markers (e.g., cortisol, amylase), they usually require a blood test. For this reason, the use of heart rate variability (HRV) to characterize stress has recently come to the fore. HRV is the variability in the length of heartbeat intervals, which indicates the ability of the heart to respond to various physiological and environmental stimuli. However, the conventional HRV metrics are not corrected for heart rate dependence; hence, they fail to fully account for the complex physiology of stress and relaxation. In order to remedy this problem, here we introduce a novel HRV parameter, the normalized variability derived from an RMSSD “Master Curve”, and we compare it with the conventional metrics. Methods: In Study 1, the relaxation state was induced either by heart rate variability biofeedback training (N = 21) or by habitual relaxation (N = 21), while in Study 2 (N = 9), the Socially Evaluated Cold Pressor Test and the Socially Evaluated Stroop Test were used to induce stress in the subject. For a statistical evaluation of the data, the Kolmogorov–Smirnov test was used to compare the distributions of mean HR, log(RMSSD), log(SDNN), and normalized variability before, during, and after relaxation and stress. Results: The results of this study indicate that while log(RMSSD) and log(SDNN) did not change significantly, the normalized variability did undergo a significant change both in relaxation states and in stress states induced by the Socially Evaluated Cold Pressor Test. Conclusions: Overall, we suggest this novel type of normalized variability ought to be used as a sensitive stress indicator, and in general, for the characterization of the complex processes of the vegetative nervous system.
Terjedelem/Fizikai jellemzők:18
ISSN:2227-9059