Cardiorespiratory Dynamic Response to Mental Stress: A Multivariate Time-Frequency Analysis

Author:

Widjaja Devy12ORCID,Orini Michele3,Vlemincx Elke4ORCID,Van Huffel Sabine12

Affiliation:

1. KU Leuven, Department of Electrical Engineering (ESAT), STADIUS, Kasteelpark Arenberg 10, P.O. Box 2446, 3001 Leuven, Belgium

2. iMinds, Future Health Department, Kasteelpark Arenberg 10, P.O. Box 2446, 3001 Leuven, Belgium

3. University College of London, Institute of Cardiovascular Science, 66 Gower Street, London WC1E 6BT, UK

4. KU Leuven, Department of Psychology and Educational Sciences, Tiensestraat 102, 3000 Leuven, Belgium

Abstract

Mental stress is a growing problem in our society. In order to deal with this, it is important to understand the underlying stress mechanisms. In this study, we aim to determine how the cardiorespiratory interactions are affected by mental arithmetic stress and attention. We conduct cross time-frequency (TF) analyses to assess the cardiorespiratory coupling. In addition, we introduce partial TF spectra to separate variations in the RR interval series that are linearly related to respiration from RR interval variations (RRV) that are not related to respiration. The performance of partial spectra is evaluated in two simulation studies. Time-varying parameters, such as instantaneous powers and frequencies, are derived from the computed spectra. Statistical analysis is carried out continuously in time to evaluate the dynamic response to mental stress and attention. The results show an increased heart and respiratory rate during stress and attention, compared to a resting condition. Also a fast reduction in vagal activity is noted. The partial TF analysis reveals a faster reduction of RRV power related to (3 s) than unrelated to (30 s) respiration, demonstrating that the autonomic response to mental stress is driven by mechanisms characterized by different temporal scales.

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modelling and Simulation,General Medicine

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