Can an automated sleep detection algorithm for waist-worn accelerometry replace sleep logs?

Tiago Barreira, Jessica Redmond, Tom D Brutsaert, John M. Schuna, Emily F. Mire, Peter T. Katzmarzyk, Catrine Tudor-Locke

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Abstract

The purpose of this study was to test whether estimates of bedtime, wake time, and sleep period time (SPT) were comparable between an automated algorithm (ALG) applied to waist-worn accelerometry data and a sleep log (LOG) in an adult sample. A total of 104 participants were asked to log evening bedtime and morning wake time and wear an ActiGraph wGT3X-BT accelerometer at their waist for 24 h/day for 7 consecutive days. Mean difference and mean absolute difference (MAD) were computed. Pearson correlations and dependent-sample t tests were used to compare LOG-based and ALG-based sleep variables. Effect sizes were calculated for variables with significant mean differences. A total of 84 participants provided 2+ days of valid accelerometer and LOG data for a total of 368 days. There was no mean difference (p = 0.47) between LOG 472 ± 59 min and ALG SPT 475 ± 66 min (MAD = 31 ± 23 min, r = 0.81). There was no significant mean difference between bedtime (2348 h and 2353 h for LOG and ALG, respectively; p = 0.14, MAD = 25 ± 21 min, r = 0.92). However, there was a significant mean difference between LOG (0741 h) and ALG (0749 h) wake times (p = 0.01, d = 0.11, MAD = 24 ± 21 min, r = 0.92). The LOG and ALG data were highly correlated and relatively small differences were present. The significant mean difference in wake time might not be practically meaningful (Cohen’s d = 0.11), making the ALG useful for sample estimates. MAD, which gives a better estimate of the expected differences at the individual level, also demonstrated good evidence supporting ALG individual estimates.

Original languageEnglish (US)
Pages (from-to)1027-1032
Number of pages6
JournalApplied Physiology, Nutrition and Metabolism
Volume43
Issue number10
DOIs
StatePublished - Jan 1 2018

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Keywords

  • Accelerometer
  • Nocturnal
  • Objectively measured

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Physiology
  • Nutrition and Dietetics
  • Physiology (medical)

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