Identifying ActiGraph non-wear time in pregnant women with overweight or obesity.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of science and medicine in sport"
DOI: 10.1016/j.jsams.2020.08.003
Abstract: OBJECTIVES Non-wear time algorithms have not been validated in pregnant women with overweight/obesity (PW-OW/OB), potentially leading to misclassification of sedentary/activity data, and inaccurate estimates of how physical activity is associated with pregnancy outcomes. We examined:… read more here.
Keywords: algorithms; pregnant women; time; min ... See more keywords
Evaluating the performance of raw and epoch non-wear algorithms using multiple accelerometers and electrocardiogram recordings
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-62821-2
Abstract: Accurate detection of accelerometer non-wear time is crucial for calculating physical activity summary statistics. In this study, we evaluated three epoch-based non-wear algorithms (Hecht, Troiano, and Choi) and one raw-based algorithm (Hees). In addition, we… read more here.
Keywords: classification; electrocardiogram recordings; wear algorithms; accelerometers electrocardiogram ... See more keywords
Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Sports Sciences"
DOI: 10.1080/02640414.2019.1703301
Abstract: ABSTRACT Detection of non-wear periods is an important step in accelerometer data processing. This study evaluated five non-wear detection algorithms for wrist accelerometer data and two rules for non-wear detection when non-wear and sleep algorithms… read more here.
Keywords: wear detection; non; accelerometer data; non wear ... See more keywords