Short-term HRV in young adults for momentary assessment of acute mental stress

Abstract Mental stress has become a major health threat in our society and its continuous monitoring and timely intervention is key to stress management. Heart rate variability (HRV) has been considered as a potential candidate for ecological momentary assessment of acute mental stress, and growing number of HRV metrics have been developed. However, inconsistency of findings in prior studies necessitates further investigation on what are the appropriate metrics in tracking the momentary variation of mental stress. This study employs a block design inducing low-high-low-high stress variation profile to test the feasibility of a broad range of HRV metrics for measuring the minute-scale stress variation elicited by the commonly used mental arithmetic tasks. After extracting the RR interval series, 42 HRV metrics have been examined in absolute reliability, relative reliability, and the statistical significance in differentiating the low and high stress levels. Among these metrics, 22 show absolute reliability, 21 show relative reliability, and 13 differentiate the low and high stress levels consistently across all four pairs of comparison. Venn’s diagram analysis resulted eight metrics hold both absolute and relative reliability, whereas those metrics robustly differentiating high and low stress levels hold either absolute (3/13) or relative (10/13) reliability. Our results show that, although not all HRV metrics hold both absolute and relative reliability, about one third of the examined HRV metrics can effectively track the variations of mental stress. These findings suggest the importance of HRV metrics selection when applied for monitoring acute mental stress.

[1]  Ana Aguiar,et al.  Heart rate variability metrics for fine-grained stress level assessment , 2017, Comput. Methods Programs Biomed..

[2]  P. Melillo,et al.  Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination , 2011, Biomedical engineering online.

[3]  C. Kirschbaum,et al.  The 'Trier Social Stress Test'--a tool for investigating psychobiological stress responses in a laboratory setting. , 1993, Neuropsychobiology.

[4]  K. Wac,et al.  Acute mental stress and surgical performance , 2018, BJS open.

[5]  G Atkinson,et al.  Statistical Methods For Assessing Measurement Error (Reliability) in Variables Relevant to Sports Medicine , 1998, Sports medicine.

[6]  J. Carter,et al.  Sympathetic neural responses to mental stress: responders, nonresponders and sex differences. , 2009, American journal of physiology. Heart and circulatory physiology.

[7]  S. Huffel,et al.  Instantaneous changes in heart rate regulation due to mental load in simulated office work , 2011, European Journal of Applied Physiology.

[8]  F. Shaffer,et al.  An Overview of Heart Rate Variability Metrics and Norms , 2017, Front. Public Health.

[9]  Rossana Castaldo,et al.  Ultra-short term HRV features as surrogates of short term HRV: a case study on mental stress detection in real life , 2019, BMC Medical Informatics and Decision Making.

[10]  S. Shiffman,et al.  Ecological momentary assessment. , 2008, Annual review of clinical psychology.

[11]  George Nikiforidis,et al.  Methodological issues in the spectral analysis of the heart rate variability: Application in patients with epilepsy , 2014, Biomed. Signal Process. Control..

[12]  Adrian Basarab,et al.  Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review , 2016, J. Biomed. Informatics.

[13]  H. Stanley,et al.  Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. , 1995, Chaos.

[14]  J. Thayer,et al.  Heart rate variability as a transdiagnostic biomarker of psychopathology. , 2015, International Journal of Psychophysiology.

[15]  V. LeBlanc The Effects of Acute Stress on Performance: Implications for Health Professions Education , 2009, Academic medicine : journal of the Association of American Medical Colleges.

[16]  Keith Willson,et al.  Physiological basis of fractal complexity properties of heart rate variability in man , 2002, The Journal of physiology.

[17]  J. B. Holzman,et al.  Heart rate variability indices as bio-markers of top-down self-regulatory mechanisms: A meta-analytic review , 2017, Neuroscience & Biobehavioral Reviews.

[18]  Stefan Sammito,et al.  The circadian rhythm of heart rate variability , 2016 .

[19]  B. Oken,et al.  Sensitivity to mental effort and test–retest reliability of heart rate variability measures in healthy seniors , 2011, Clinical Neurophysiology.

[20]  G. Billman The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance , 2013, Front. Physio..

[21]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[22]  K. Chon,et al.  Approximate entropy for all signals , 2009, IEEE Engineering in Medicine and Biology Magazine.

[23]  John T. Cacioppo,et al.  Heart Rate Variability: Stress and Psychiatric Conditions , 2007 .

[24]  D. Sanabria,et al.  Heart rate variability and cognitive processing: The autonomic response to task demands , 2016, Biological Psychology.

[25]  Elizabeth Tharion,et al.  Short-term heart rate variability measures in students during examinations. , 2009, The National medical journal of India.

[26]  Atefeh Goshvarpour,et al.  Do men and women have different ECG responses to sad pictures? , 2017, Biomed. Signal Process. Control..

[27]  Lionel Tarassenko,et al.  Quantifying errors in spectral estimates of HRV due to beat replacement and resampling , 2005, IEEE Transactions on Biomedical Engineering.

[28]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[29]  A. Wykrętowicz,et al.  Correlations between the Poincaré plot and conventional heart rate variability parameters assessed during paced breathing. , 2007, The journal of physiological sciences : JPS.

[30]  B. Takase,et al.  Prognostic value of heart rate variability in comparison with annual health examinations in very elderly subjects. , 2013, Journal of Nippon Medical School = Nippon Ika Daigaku zasshi.

[31]  C. M. Lim,et al.  Application of higher order statistics/spectra in biomedical signals--a review. , 2010, Medical engineering & physics.

[32]  D. Berckmans,et al.  Heart rate and high frequency heart rate variability during stress as biomarker for clinical depression. A systematic review , 2018, Psychological Medicine.

[33]  Seong-Eun Moon,et al.  Implicit Analysis of Perceptual Multimedia Experience Based on Physiological Response: A Review , 2017, IEEE Transactions on Multimedia.

[34]  M. Siepmann,et al.  The Effects of Psychosocial Stress on Heart Rate Variability in Panic Disorder , 2010 .

[35]  Andrew Steptoe,et al.  Effects of stress on the development and progression of cardiovascular disease , 2018, Nature Reviews Cardiology.

[36]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[37]  Yuli Huang,et al.  Perceived stress status and sympathetic nervous system activation in young male patients with coronary artery disease in China. , 2015, European journal of internal medicine.

[38]  Rossana Castaldo,et al.  Acute mental stress assessment via short term HRV analysis in healthy adults: A systematic review with meta-analysis , 2015, Biomed. Signal Process. Control..

[39]  M. Murugappan,et al.  Classification of emotional states from electrocardiogram signals: a non-linear approach based on hurst , 2013, BioMedical Engineering OnLine.

[40]  Luca Faes,et al.  Comparison of short-term heart rate variability indexes evaluated through electrocardiographic and continuous blood pressure monitoring , 2019, Medical & Biological Engineering & Computing.

[41]  Sazali Yaacob,et al.  Multiple Physiological Signal-Based Human Stress Identification Using Non-Linear Classifiers , 2013 .

[42]  K. Dedovic,et al.  The Montreal Imaging Stress Task: using functional imaging to investigate the effects of perceiving and processing psychosocial stress in the human brain. , 2005, Journal of psychiatry & neuroscience : JPN.

[43]  N. Withofs,et al.  Circadian rhythm of heart rate and heart rate variability , 2000, Archives of disease in childhood.

[44]  Dimitrios Soulis,et al.  Assessment of arterial baroreflex sensitivity by different computational analyses of pressure wave signals alone , 2019, Comput. Methods Programs Biomed..

[45]  Marimuthu Palaniswami,et al.  Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability? , 2001, IEEE Transactions on Biomedical Engineering.

[46]  J. Zbilut,et al.  Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals. , 2002, Medical engineering & physics.

[47]  W. Bardwell,et al.  Effects of stress on heart rate complexity—A comparison between short-term and chronic stress , 2009, Biological Psychology.

[48]  T. Mikako,et al.  Biomedical Research , 2007 .

[49]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[50]  Mickaël Causse,et al.  Neural and psychophysiological correlates of human performance under stress and high mental workload , 2016, Biological Psychology.

[51]  J. Scargle Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data , 1982 .

[52]  Marimuthu Palaniswami,et al.  Poincaré plot interpretation using a physiological model of HRV based on a network of oscillators. , 2002, American journal of physiology. Heart and circulatory physiology.