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Efficacy of Time- and Frequency-Domain Heart Rate Variability Features in Stress Detection and Their Relation with Coping Strategies

  • Pierluigi RealiEmail author
  • Agostino Brugnera
  • Angelo Compare
  • Anna Maria Bianchi
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 76)

Abstract

Heart Rate Variability (HRV) is a reliable biomarker of the Autonomic Nervous System (ANS) activity and it is widely used to characterize the stress response induced by different laboratory stress tasks. Even if acute stress responses have been previously investigated, researchers are still wondering which HRV indices are more effective for stress assessment. In the present study, we extracted several time- and frequency-domain HRV parameters and investigated which ones are better able to discriminate between a stressful and a non-stressful condition. Moreover, we explored the possibility of a linear correlation between such parameters and certain coping strategies, during three laboratory stress tasks (Montreal Imaging Stress Task, Stroop Color-Word, Speech). The effect size computed for each considered HRV parameter indicate that the average RR interval and the normalized power in low frequency (LF) band were the most effective parameters for the detection of mental stress. As regards the second hypothesis, normalized power in high frequency (HF) band during Speech was found significantly and negatively correlated with specific subscales of the administered questionnaires (CERQ-S and COPE-NVI), suggesting a possible association between the higher use of social support (SS) and other blame (OB) coping strategies and stronger autonomic responses during the Speech task.

Keywords

Heart Rate Variability Stress Coping strategies 

Notes

Acknowledgements

P. R. thanks LINK project (H2020 Grant Agreement No. 692023) for the given support.

Conflicts of Interest

The authors declare no conflicts of interest.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Electronics Information and BioengineeringPolitecnico di MilanoMilanItaly
  2. 2.Department of Human and Social SciencesUniversity of BergamoBergamoItaly

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