Associations between Sleep Quality and Heart Rate Variability: Implications for a Biological Model of Stress Detection Using Wearable Technology

Taryn Chalmers, Blake A. Hickey, Philip Newton, Chin-Teng Lin, David Sibbritt, Craig S. McLachlan, Roderick Clifton-Bligh, John W. Morley and Sara Lal
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Taryn Chalmers: Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, Broadway, Sydney, NSW 2007, Australia
Blake A. Hickey: Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, Broadway, Sydney, NSW 2007, Australia
Philip Newton: School of Nursing and Midwifery, Western Sydney University, Penrith, NSW 2747, Australia
Chin-Teng Lin: Australian AI Institute, University of Technology Sydney, Broadway, Sydney, NSW 2007, Australia
David Sibbritt: School of Public Health, University of Technology Sydney, Broadway, Sydney, NSW 2007, Australia
Craig S. McLachlan: Centre for Healthy Futures, Torrens University, Sydney, NSW 2009, Australia
Roderick Clifton-Bligh: Kolling Institute for Medical Research, Royal North Shore Hospital, St Leonards, NSW 2064, Australia
John W. Morley: School of Medicine, Western Sydney University, Penrith, NSW 2747, Australia
Sara Lal: Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, Broadway, Sydney, NSW 2007, Australia

IJERPH, 2022, vol. 19, issue 9, 1-10

Abstract: Introduction: The autonomic nervous system plays a vital role in the modulation of many vital bodily functions, one of which is sleep and wakefulness. Many studies have investigated the link between autonomic dysfunction and sleep cycles; however, few studies have investigated the links between short-term sleep health, as determined by the Pittsburgh Quality of Sleep Index (PSQI), such as subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction, and autonomic functioning in healthy individuals. Aim: In this cross-sectional study, the aim was to investigate the links between short-term sleep quality and duration, and heart rate variability in 60 healthy individuals, in order to provide useful information about the effects of stress and sleep on heart rate variability (HRV) indices, which in turn could be integrated into biological models for wearable devices. Methods: Sleep parameters were collected from participants on commencement of the study, and HRV was derived using an electrocardiogram (ECG) during a resting and stress task (Trier Stress Test). Result: Low-frequency to high-frequency (LF:HF) ratio was significantly higher during the stress task than during the baseline resting phase, and very-low-frequency and high-frequency HRV were inversely related to impaired sleep during stress tasks. Conclusion: Given the ubiquitous nature of wearable technologies for monitoring health states, in particular HRV, it is important to consider the impacts of sleep states when using these technologies to interpret data. Very-low-frequency HRV during the stress task was found to be inversely related to three negative sleep indices: sleep quality, daytime dysfunction, and global sleep score.

Keywords: rate variability; sleep; stress; wearable technology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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