Is it on? An algorithm for discerning wrist-accelerometer non-wear times from sleep/wake activity

Chronobiol Int. 2016;33(6):599-603. doi: 10.3109/07420528.2016.1167720. Epub 2016 Apr 20.

Abstract

The accuracy of sleep/wake estimates derived with actigraphy is often dependent on researchers being able to discern non-wear times from sleep or quiescent wakefulness when confronted by discrepancies in a sleep log. Without knowing when an accelerometer is being worn, non-wear could be inferred from periods of inactivity unlikely to occur while in bed. Data collected in our laboratory suggest that more than 50% of inactive periods during time in bed are <8 min in duration. This duration may be an appropriate minimum threshold for routine non-wear classification during self-reported wake. Higher thresholds could be chosen to derive non-wear definitions for self-reported bedtimes depending on the desired level of certainty. To determine non-wear at thresholds of 75%, 95% and 99%, for example, would require periods of inactivity lasting ≥18 min, ≥53 min and ≥85 min, respectively.

Keywords: Actigraphy; activity cycles; biostatistics; nonwear; physical activity; sedentary behavior; sleep.

MeSH terms

  • Actigraphy / methods
  • Adult
  • Algorithms*
  • Circadian Rhythm / physiology*
  • Humans
  • Male
  • Monitoring, Ambulatory
  • Motor Activity / physiology
  • Self Report
  • Sleep / physiology*
  • Time Factors
  • Wakefulness / physiology*
  • Wrist
  • Young Adult