Journal: BMC Medical Research Methodology volume
All Authors: Adam Vert, Kyle S. Weber, Vanessa Thai, Erin Turner, Kit B. Beyer, Benjamin F Cornish, F. Elizabeth Godkin, Christopher Wong, William E. McIlroy & Karen Van Ooteghem
Accelerometery is commonly used to estimate physical activity, sleep, and sedentary behavior. In free-living conditions, periods of device removal (non-wear) can lead to misclassification of behavior with consequences for research outcomes and clinical decision making. Common methods for non-wear detection are limited by data transformations (e.g., activity counts) or algorithm parameters such as minimum durations or absolute temperature thresholds that risk over- or under-estimating non-wear time. This study aimed to advance non-wear detection methods by integrating a ‘rate-of-change’ criterion for temperature into a combined temperature-acceleration algorithm.