Cargando…
Evaluating the performance of raw and epoch non-wear algorithms using multiple accelerometers and electrocardiogram recordings
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 performed a sensitivity analysis to prov...
Autores principales: | Syed, Shaheen, Morseth, Bente, Hopstock, Laila A., Horsch, Alexander |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125135/ https://www.ncbi.nlm.nih.gov/pubmed/32246080 http://dx.doi.org/10.1038/s41598-020-62821-2 |
Ejemplares similares
-
A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks
por: Syed, Shaheen, et al.
Publicado: (2021) -
Correction: Time trends in physical activity in the Tromsø study: An update
por: Morseth, Bente, et al.
Publicado: (2020) -
Time trends in physical activity in the Tromsø study: An update
por: Morseth, Bente, et al.
Publicado: (2020) -
Multiple imputation approaches for epoch-level accelerometer data in trials
por: Tackney, Mia S, et al.
Publicado: (2023) -
Effects of Varying Epoch Lengths, Wear Time Algorithms, and Activity Cut-Points on Estimates of Child Sedentary Behavior and Physical Activity from Accelerometer Data
por: Banda, Jorge A., et al.
Publicado: (2016)