Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Oct 1, 2020
Date Accepted: Dec 23, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Heart rate variability and sleep: Validity of Firstbeat method in detecting sleep stages in healthy young adults
ABSTRACT
Background:
Wearable devices are used for providing objective markers of sleep.
Objective:
We examined the validity of heart rate variability based Firstbeat sleep analysis method (FB) against polysomnography (PSG) in a sample of healthy adults.
Methods:
Twenty adults (mean age 24.5 years, standard deviation (SD) 3.5, range 20–37 years; 50% females) wore a Firstbeat Bodyguard 2 measurement device and a Geneactiv actigraph and had an ambulatory SomnoMedics polysomnography measurement for two consecutive nights. We compared wake, combined Stage 1 (N1) and Stage 2 (N2), Stage 3 (N3; slow wave sleep, SWS) and rapid eye movement (REM) sleep between FB and PSG. We calculated sensitivity, specificity, and accuracy from the 30 sec epoch-by-epoch data.
Results:
We found that comparing FB against PSG yielded in good specificity (.75), excellent sensitivity (.95) and accuracy (.93) in detecting wake. Combined N1+N2 sleep was detected with .70 specificity, .66 sensitivity, and .69 accuracy. SWS was detected with .91 specificity, .72 sensitivity, and .87 accuracy. REM sleep was detected with .92 specificity, .59 sensitivity, and .84 accuracy. There were two measures that differed significantly between FB and PSG: FB underestimated REM sleep (mean 19 minutes, P=.025) and overestimated wake (mean 12.8 minutes, P<.001).
Conclusions:
This study supports the concept of utilizing HRV as a means for distinguishing sleep from wake and suggests that HRV is a useful marker in distinguishing different sleep stages.
Citation
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