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is hypothesized that a greater proportion of high- to low-frequency EEG signals


might indicate‘bad’sleep (as it is more similar to the EEG frequencies during


waking), no clinical significance has yet been attached to these different frequencies


or their amounts, although some patterns of NREM EEG activity have been


associated with insomnia in patients with no other sleep pathology. Spectral indices


may therefore have some potential as objective correlates of‘sleep quality’ratings


in terms of being more sensitive indicators of the nature or depth of sleep (Krystal


and Edinger 2008 ). Although increasingly research is using this technique (Zhang


et al. 2008 ; Ronai et al. 2013 ; Chamorro et al. 2013 ), the methods have yet to be


standardized.


Another potential measure of the nature or depth of sleep that is of interest as a


means for quantifying sleep quality is theCyclic Alternating Pattern (CAP),


which uses PSG data to reflect NREM sleep state instability. CAP rate has been


hypothesized to reflect the mechanisms that control arousal level during sleep


(Terzano et al. 1985 ). Increased CAP rate is significantly more common in indi-


viduals with insomnia and sleep apnea than in normal sleepers, and improvements


in CAP rate with therapy have been observed (Terzano et al. 1990 ; Terzano and


Parrino 1992 ). CAP rate was found to be the strongest correlate of‘sleep quality’


ratings by insomnia sufferers (Terzano et al. 2003 ) and therefore appears promising


as a measure of sleep quality by potentially capturing aspects of sleep not quantified


by other means (Krystal and Edinger 2008 ). The major limitation of CAP is the


relatively limited amount of research carried out, but it is becoming an increasingly
popular tool (Nasi et al. 2012 ; Chamorro et al. 2013 ).


For the purposes of anthropologicalfieldwork and research in non-clinical,


non-laboratory-based settings,actigraphyhas become increasingly popular for


assessing sleep quantity. An actigraph is a small wrist-worn device that measures


movement as a proxy for wakefulness (Acebo and LeBourgeois 2006 ). As quiet


wakefulness is likely to be recorded as sleep by actigraphy algorithms, these


devices are not particularly useful for assessing insomnia, but they are useful for


capturing data about normal sleep duration and patterning in ecologically valid


settings (de Souza et al. 2003 ; Ancoli-Israel et al. 2003 ; Njamnshi et al. 2012 ; Jones


and Ball 2014 ). There are various devices, all using different scoring algorithms that


have not been cross-validated, so they are best used for measures of sleep quantity


or timing than for assessment of sleep depth or quality and are particularly useful


for within study comparisons of sleep patterning, duration, and fragmentation.


Objective techniques are therefore well established for the assessment of sleep


duration and patterning (sleep quantity), and these are becoming more sophisticated


with advances in technology. It is important to note, however, that the quantitative


assessment of sleep is unable to provide complete information on the experience of


sleep loss. For measuring sleep quality, several challenges also remain. In


reviewing objective measures of sleep quality Krystal and Edinger ( 2008 )


emphasized (a) that subjective ratings of‘sleep quality’reflect not only quantifiable


aspects of the sleep experience, but also non-sleep phenomena that objective sleep


monitoring devices cannot capture, and (b) that‘sleep quality’may mean different
things to different people (influenced by factors such as personality traits and health


32 A.E.F. Rudzik and H.L. Ball

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