ABC | Volume 113, Nº4, October 2019

Original Article Sánchez-Hechavarría et al. Inequality in HRV spectrum for evaluation of mental stress Arq Bras Cardiol. 2019; 113(4):725-733 1. Kim HG, Cheon EJ, Bai DS, Lee YH, Koo BH. Stress and heart rate variability: a meta-analysis and review of the literature. Psychiatry Investig. 2018;15(3):235-45. 2. Chida Y, Steptoe A. Greater cardiovascular responses to laboratory mental stress are associatedwith poor subsequent cardiovascular risk status: ameta- analysis of prospective evidence. Hypertension. 2010;55(4):1026-32. 3. Bali A, Jaggi AS. Clinical experimental stress studies: methods and assessment. Rev Neurosci. 2015;26(5):555-79. 4. Heartratevariability:standardsofmeasurement,physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996;93(5):1043-65. 5. Draghici AE, Taylor JA. The physiological basis and measurement of heart rate variability in humans. J Physiol Anthropol. 2016;35(1):22. 6. Shaffer F, Ginsberg JP. An Overview of heart rate variability metrics and norms. Front Public Health. 2017 Sep 28;5:258. 7. Billman GE, Huikuri HV, Sacha J, Trimmel K. An introduction to heart rate variability: methodological considerations and clinical applications. Front Physiol. 2015 Feb 25;6:55. 8. Sztajzel J. Heart rate variability: a noninvasive electrocardiographicmethod tomeasure the autonomic nervous system. Swiss MedWkly. 2004;134(35- 36):514-22. 9. Ernst G. Heart-Rate Variability-More thanHeart Beats? Front Public Health. 2017 Sep 11;5:240. 10. Berntson GG, Bigger JT Jr, Eckberg DL, Grossman P, Kaufmann PG, Malik M, et al. Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology. 1997;34(6):623-48. 11. Akselrod S, Gordon D, Ubel FA, Shannon DC, Berger AC, Cohen RJ. Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to- beat cardiovascular control. science. 1981;213(4504):220-2. 12. Bravi A, Longtin A, Seely AJ. Review and classification of variability analysis techniqueswithclinicalapplications.BiomedEngOnline.2011Oct10;10:90. References Conclusions This study successfully applied Gini coefficient to power spectral densities of HRV to measure the inequality in distribution of frequency bands. These results suggest that during stress (arithmetic challenge), compared to rest, not only total power of low frequency band increases, but the total power distribution becomesmore unequal. Spectral inequalities of heart rate variability analyzed from the Gini coefficient seem to be independent and homogeneous indicators of psychophysiological mental stress compared to traditional indices of HRV as per this pilot study. Out of traditional and spectral Gini indices of HRV, HR, LF/HF, SpG (LF) seems to be valid and reliable tools as indicators of stress, and this study provides cutoff values for these variables to discriminate the states of stress and rest. Study limitations Among the limitations of this study, the small sample size can be cited. This is a pilot study on Gini coefficient application to HRV spectrum, therefore more studies with larger sample sizes are recommended for better understanding and interpretation of inequalities in power spectral density of RR intervals. In addition, a mental arithmetic challenge was used to induce mental stress. Although thismethod is considered validand reliable, results can possibly be varied under different circumstances, as mental stress is a complex and dynamic phenomenon. Finally, HRV can be influenced by hormones depending on the menstrual phase in female participants. Although the menstrual phase was not monitored, data for both conditions (rest and mental stress) were collected on the same day in order to minimize baseline variability. Author contributions Conception and design of the research and Critical revision of the manuscript for intellectual content: Sánchez‑Hechavarría ME, Ghiya S, Carrazana-Escalona R, Cortina-Reyna S, Andreu-Heredia A, Acosta-Batista C, Saá- Muñoz NA; Acquisition of data: Sánchez-Hechavarría ME, Ghiya S, Carrazana-Escalona R, Cortina-Reyna S, Andreu- Heredia A; Analysis and interpretation of the data: Sánchez- Hechavarría ME, Ghiya S, Carrazana-Escalona R, Cortina- Reyna S, Acosta-Batista C; Statistical analysis: Sánchez- Hechavarría ME, Andreu-Heredia A, Saá-Muñoz NA; Writing of the manuscript: Sánchez-Hechavarría ME, Ghiya S, Acosta-Batista C, Saá-Muñoz NA. Potential Conflict of Interest No potential conflict of interest relevant to this article was reported. Sources of Funding There were no external funding sources for this study. Study Association This study is not associatedwith any thesis or dissertationwork. Ethical approval and informed consent This studywas approved by theMedical University of Santiago de Cuba Ethics Committee under protocol number 22/2017. All procedures involved in this study are in accordance with the 1975 Helsinki Declaration, updated in 2013. Informed consent was obtained from all participants included in the study. 731