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Heart rate variability in normal and pathological sleep

期刊

FRONTIERS IN PHYSIOLOGY
卷 4, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fphys.2013.00294

关键词

autonomic nervous system; heart rate variability; sleep; non-linear analysis; obstructive sleep apnea; insomnia; SUDEP

资金

  1. European Regional Development Fund-Project FNUSA-ICRC [CZ.1.05/1.1.00/02.0123]

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Sleep is a physiological process involving different biological systems, from molecular to organ level; its integrity is essential for maintaining health and homeostasis in human beings. Although in the past sleep has been considered a state of quiet, experimental and clinical evidences suggest a noteworthy activation of different biological systems during sleep. A key role is played by the autonomic nervous system (ANS), whose modulation regulates cardiovascular functions during sleep onset and different sleep stages. Therefore, an interest on the evaluation of autonomic cardiovascular control in health and disease is growing by means of linear and non-linear heart rate variability (HRV) analyses. The application of classical tools for ANS analysis, such as HRV during physiological sleep, showed that the rapid eye movement (REM) stage is characterized by a likely sympathetic predominance associated with a vagal withdrawal, while the opposite trend is observed during non-REM sleep. More recently, the use of non-linear tools, such as entropy-derived indices, have provided new insight on the cardiac autonomic regulation, revealing for instance changes in the cardiovascular complexity during REM sleep, supporting the hypothesis of a reduced capability of the cardiovascular system to deal with stress challenges. Interestingly, different HRV tools have been applied to characterize autonomic cardiac control in different pathological conditions, from neurological sleep disorders to sleep disordered breathing (SDB). In summary, linear and non-linear analysis of HRV are reliable approaches to assess changes of autonomic cardiac modulation during sleep both in health and diseases. The use of these tools could provide important information of clinical and prognostic relevance.

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