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Abstract

Introduction
Sleep-wake state discrepancy, the mismatch between subjective and objective measurements of sleep/wake status, is estimated to affect 9-50% of individuals with insomnia, often undetected due to lack of objective measures. Consumer sleep devices allow efficient measurement of sleep-wake state across multiple nights in the habitual sleep environment. This study assessed sleep-wake state discrepancies obtained by two devices across multiple nights in individuals with insomnia.

Methods
Individuals with insomnia completed daily sleep diaries, wore a Fitbit Charge 4 device, and used a Withings Sleep Analyser under-mattress sensor for 14-days. Sleep metrics were obtained from all three data sources to calculate sleep-wake state discrepancy (device metric − diary metric).

Results
15 people participated in the study. Fitbit data were available for 12 and mattress data for 11 participants. There were no significant differences between the sleep-wake state discrepancy values derived from Fitbit and Withings devices for total sleep time (−78.7±111.8 and −95.7±124.4 minutes respectively; p .123) or wake after sleep onset (−15.4±52.9 and −17.6±110.6 minutes respectively; p .826). Significant differences were found in the sleep-wake state discrepancy values derived from Fitbit (−17.5±23.3, p <.001) and Withings devices for number of awakenings (3.2±23.1, p .175).

Discussion
Both devices comparably detected sleep-wake state discrepancy in people with insomnia, noting a device-difference for number of awakenings. These preliminary findings suggest that consumer devices may be useful to detect sleep-wake state discrepancy. Larger studies may reveal devices do so with different levels of sensitivity. Future studies should include polysomnography to assess relative magnitudes across devices.
Original languageEnglish
Article numberO036
Pages (from-to)A12–A13
Number of pages2
JournalSleep Advances
Volume4
Issue numberSupplement 1
DOIs
Publication statusPublished - Oct 2023

Keywords

  • polysomnography
  • sleep
  • insomnia
  • medical devices
  • sensor
  • sleep diary
  • mismatch
  • fitness trackers

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