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Visibility graph analysis of very short-term heart rate variability during sleep

Author

Listed:
  • Hou, F.Z.
  • Li, F.W.
  • Wang, J.
  • Yan, F.R.

Abstract

Based on a visibility-graph algorithm, complex networks were constructed from very short-term heart rate variability (HRV) during different sleep stages. Network measurements progressively changed from rapid eye movement (REM) sleep to light sleep and then deep sleep, exhibiting promising ability for sleep assessment. Abnormal activation of the cardiovascular controls with enhanced ‘small-world’ couplings and altered fractal organization during REM sleep indicates that REM could be a potential risk factor for adverse cardiovascular event, especially in males, older individuals, and people who are overweight. Additionally, an apparent influence of gender, aging, and obesity on sleep was demonstrated in healthy adults, which may be helpful for establishing expected sleep-HRV patterns in different populations.

Suggested Citation

  • Hou, F.Z. & Li, F.W. & Wang, J. & Yan, F.R., 2016. "Visibility graph analysis of very short-term heart rate variability during sleep," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 140-145.
    • Handle: RePEc:eee:phsmap:v:458:y:2016:i:c:p:140-145
    DOI: 10.1016/j.physa.2016.03.086
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    Citations

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    Cited by:

    1. Flori, Andrea & Pammolli, Fabio & Spelta, Alessandro, 2021. "Commodity prices co-movements and financial stability: A multidimensional visibility nexus with climate conditions," Journal of Financial Stability, Elsevier, vol. 54(C).
    2. Xu, Paiheng & Zhang, Rong & Deng, Yong, 2017. "A novel weight determination method for time series data aggregation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 42-55.
    3. Xu, Paiheng & Zhang, Rong & Deng, Yong, 2018. "A novel visibility graph transformation of time series into weighted networks," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 201-208.

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