Journal of Sleep and Sleep Disorder Research
ISSN: 2574-4518
Current Issue
Volume No: 1 Issue No: 3
share this page

Editorial | Open Access
  • Available online freely | Peer Reviewed
  • How to Objectively Measure The Quality of Sleep

    Diego Liberati 1      

    1 National Research Council of Italy

    Received 13 Aug 2018; Accepted 30 Aug 2018; Published 01 Sep 2018;

    Academic Editor:Karim Sedky, Cooper Hospital-Rowan University, United states.

    Checked for plagiarism: Yes

    Review by: Single-blind

    Copyright 2018 Diego Liberati

    License
    Creative Commons License    This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Competing interests

    The authors have declared that no competing interests exist.

    Citation:

    Diego Liberati (2018) How to Objectively Measure The Quality of Sleep . Journal of Sleep and Sleep Disorder Research - 1(3):14-15.
    Download as RIS, BibTeX, Text (Include abstract )
    DOI10.14302/issn.2574-4518.jsdr-18-2302

    Introduction

    Sleep is of paramount importance for resetting brain and body function. While new borns tend to sleep most of their day hours, geriatric population often suffers of lack of enough sleep.

    Most of the people will subjectively complain about their sleep, at least at one point in their life. While life requirements and schedule might play a major aspect in this, other sleep disorders should be ruled out.

    There is thus a need to use objective measures to better assess sleep quality and quantity. We will briefly review some of the most interesting in our opinion. First of all actigrafy, the most simple but still quite informative: during sleep we tend to move less than awake: by measuring the sequences of lengths of intervals with no moving besides breath we could grasp quite a lot of information about how much and how often we sleep.

    Hearth rate variability (HRV) (Circulation 91) is a simple and powerful stress quantifier, both in acute and chronic: sympatho-vagal balance is perfectly described by the relative amount of low and high frequency components in the HRV spectrum.

    Thus, a low or impaired HRV signifies high risk of cardiovascular complications and even death. It can be impaired in individuals with insomnia and those having obstructive sleep apnea A bit more invasive, needing blood samples, is the hormone deconvolution (IEEE Trans Biomedical Engineering 1993) in order to assess the inaccessible and even Nano-metric pituitary secretion driving hormone feedback loops: growth hormone peaks are known to be synchronous with dreams at about 90 minutes distances.

    It is important to measure hormone course: for example: GH surge has been correlated with the onset of stage 3 and 4, with few minute delay.

    Central Nervous System analysis via Electroencephalogram or Near Infra Red Spectra (Magnetoencephalograms and functional Magnetic Resonance Imaging seem out of ergonomy) looks a bit less comfortable, but coherence among different brain areas activation (Neuroimage 2007) is quite helpful in describing our not just conscious behaviour.

    In particular, NIRS is a modality to measure the cerebral hemodynamic properties through assessing oxygenation state of the haemoglobin. This latter measure has been correlated to the cerebral blood flow and its oxygen metabolic rate. During sleep, an increased oxygenation level was found during REM compared to a decrease during slow wave stage.

    Such a simple battery of consolidated tools, in addition to the standard quali-quantitative observation (not discussed here), could be of great help in better objectively assess quality and quantity of sleep, in order to better diagnose and even monitory therapies also in sleep disorders