Relevance of Frequency of Heart-Rate Peaks as Indicator of ‘Biological’ Stress Level
The biopsychosocial (BPS) model proposes that health is best understood as a combination of bio-physiological, psychological and social determinants, and thus advocates for a far more comprehensive investigation of the relationships between ‘mind-body’ health. For this holistic analysis, we need a suitable measure to indicate participants’ ‘biological’ stress. With the advent of wearable sensor devices, health monitoring is becoming easier. In this study, we focus on bio-physiological indicators of stress, from wearable devices using the heart-rate data. The analysis of such heart-rate data presents a set of practical challenges. We review various measures currently in use for stress measurement and their relevance and significance with the wearables’ heart-rate data. In this paper, we propose to use the novel ‘peak heart-rate count’ metric to quantify level of ‘biological’ stress. Real life biometric data obtained from digital health intervention program was considered for the study. Our study indicates the significance of using frequency of ‘peak heart-rate count’ as a ‘biological’ stress measure.
KeywordsBiopsychosocial model Bio-physiological data Wearable Heart-rate ‘Heart-rate peak count’ ‘Biological’ stress Biometric Big data
The authors wish to acknowledge, Faculty of Health, Federation University Australia and Australian Government Research Training Program for supporting this research.
- 1.Ahmed, M.U., Begum, S., Islam, M.S.: Heart Rate and Inter-Beat Interval Computation to Diagnose Stress Using ECG Sensor Signal. Report 1929, Mälardalen University, Västerås, Sweden (2010)Google Scholar
- 9.Nikolopoulos, S., Alexandridi, A., Nikolakeas, S., Manis, G.: Experimental analysis of heart rate variability of long-recording electrocardiograms in normal subjects and patients with coronary artery disease and normal left ventricular function. J. Biomed. Inform. 36(3), 202–217 (2003)CrossRefGoogle Scholar
- 10.Priest, J.B., Roberson, P.N., Woods, S.B.: In our lives and under our skin an investigation of specific psycho-biological mediators linking family relationships and health using the biobehavioural family model. Family Process (2018). https://doi.org/10.1111/famp.12357
- 11.Rebergen, D., Nagaraj, S., Rosenthal, E., Bianchi, M., van Putten, M., Westover, M.: Adarri: a novel method to detect spurious r-peaks in the electrocardiogram for heart rate variability analysis in the intensive care unit. J. Clin. Monit. Comput. 32(1), 53–61 (2018). http://www.es.mdh.se/publications/1929-CrossRefGoogle Scholar
- 13.Sano, A., Taylor, S.M., McHill, A.W., Barger, L.K., Klerman, E., Picard, R.: Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018). https://doi.org/10.2196/jmir.9410CrossRefGoogle Scholar
- 14.Selye, H.: The Stress of Life. McGraw-Hill, New York (1956)Google Scholar
- 15.Sharashova, E.: Decline in Resting Heart Rate, its Association with Other Variables, and its Role in Cardiovascular Disease. Thesis, pp. 1–81 (2016)Google Scholar
- 16.Williams, D., Cash, C., Rankin, C., Bernardi, A., Koenig, J., Thayer, J.: Resting heart rate variability predicts self-reported difficulties in emotion regulation: a focus on different facets of emotion regulation. Front. Psychol. 6 (2018)Google Scholar