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

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
• nonwear
• physical activity
• sedentary behavior
• biostatistics
• sleep

Acknowledgments

The authors would like to thank Dr Charli Sargent and all the students and research staff who assisted with data collection.

Declaration of interest

The authors have no conflicts of interest related to this article. This study was financially supported by a Discovery Project grant from the Australian Research Council.