Prediction models discriminating between nonlocomotive and locomotive activities in children using a triaxial accelerometer with a gravity-removal physical activity classification algorithm.
The aims of our study were to examine whether a gravity-removal physical activity classification algorithm (GRPACA) is applicable for discrimination between nonlocomotive and locomotive activities for various physical activities (PAs) of children and to prove that this approach improves the estimati...
Main Authors: | Yuki Hikihara, Chiaki Tanaka, Yoshitake Oshima, Kazunori Ohkawara, Kazuko Ishikawa-Takata, Shigeho Tanaka |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2014-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3995680?pdf=render |
Similar Items
-
Estimating model of sedentary behavior with tri-axial accelerometer in elementary school children
by: Yuki Hikihara, et al.
Published: (2021-03-01) -
How much locomotive activity is needed for an active physical activity level: analysis of total step counts
by: Ohkawara Kazunori, et al.
Published: (2011-11-01) -
Prediction of the Physical Activity Level of Community-Dwelling Older Japanese Adults with a Triaxial Accelerometer Containing a Classification Algorithm for Ambulatory and Non-Ambulatory Activities
by: Shigeho Tanaka, et al.
Published: (2023-05-01) -
Deep Activity Recognition Models with Triaxial Accelerometers
by: Abu Alsheikh, Mohammad, et al.
Published: (2017) -
Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study
by: Murakami, Haruka, et al.
Published: (2019-08-01)