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Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities

Although accelerometry data are widely utilized to estimate physical activity and sedentary behavior among children age 3 years or older, for toddlers age 1 and 2 year(s), accelerometry data recorded during such behaviors have been far less examined. In particular, toddler’s unique behaviors, such a...

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Autores principales: Kwon, Soyang, Zavos, Patricia, Nickele, Katherine, Sugianto, Albert, Albert, Mark V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678133/
https://www.ncbi.nlm.nih.gov/pubmed/31330889
http://dx.doi.org/10.3390/ijerph16142598
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author Kwon, Soyang
Zavos, Patricia
Nickele, Katherine
Sugianto, Albert
Albert, Mark V.
author_facet Kwon, Soyang
Zavos, Patricia
Nickele, Katherine
Sugianto, Albert
Albert, Mark V.
author_sort Kwon, Soyang
collection PubMed
description Although accelerometry data are widely utilized to estimate physical activity and sedentary behavior among children age 3 years or older, for toddlers age 1 and 2 year(s), accelerometry data recorded during such behaviors have been far less examined. In particular, toddler’s unique behaviors, such as riding in a stroller or being carried by an adult, have not yet been examined. The objective of this study was to describe accelerometry signal outputs recorded during participation in nine types of behaviors (i.e., running, walking, climbing up/down, crawling, riding a ride-on toy, standing, sitting, riding in a stroller/wagon, and being carried by an adult) among toddlers. Twenty-four toddlers aged 13 to 35 months (50% girls) performed various prescribed behaviors during free play in a commercial indoor playroom while wearing ActiGraph wGT3X-BT accelerometers on a hip and a wrist. Participants’ performances were video-recorded. Based on the video data, accelerometer data were annotated with behavior labels to examine accelerometry signal outputs while performing the nine types of behaviors. Accelerometer data collected during 664 behavior assessments from the 21 participants were used for analysis. Hip vertical axis counts for walking were low (median = 49 counts/5 s). They were significantly lower than those recorded while a toddler was “carried” by an adult (median = 144 counts/5 s; p < 0.01). While standing, sitting, and riding in a stroller, very low hip vertical axis counts were registered (median ≤ 5 counts/5 s). Although wrist vertical axis and vector magnitude counts for “carried” were not higher than those for walking, they were higher than the cut-points for sedentary behaviors. Using various accelerometry signal features, machine learning techniques showed 89% accuracy to differentiate the “carried” behavior from ambulatory movements such as running, walking, crawling, and climbing. In conclusion, hip vertical axis counts alone may be unable to capture walking as physical activity and “carried” as sedentary behavior among toddlers. Machine learning techniques that utilize additional accelerometry signal features could help to recognize behavior types, especially to differentiate being “carried” from ambulatory movements.
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spelling pubmed-66781332019-08-19 Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities Kwon, Soyang Zavos, Patricia Nickele, Katherine Sugianto, Albert Albert, Mark V. Int J Environ Res Public Health Article Although accelerometry data are widely utilized to estimate physical activity and sedentary behavior among children age 3 years or older, for toddlers age 1 and 2 year(s), accelerometry data recorded during such behaviors have been far less examined. In particular, toddler’s unique behaviors, such as riding in a stroller or being carried by an adult, have not yet been examined. The objective of this study was to describe accelerometry signal outputs recorded during participation in nine types of behaviors (i.e., running, walking, climbing up/down, crawling, riding a ride-on toy, standing, sitting, riding in a stroller/wagon, and being carried by an adult) among toddlers. Twenty-four toddlers aged 13 to 35 months (50% girls) performed various prescribed behaviors during free play in a commercial indoor playroom while wearing ActiGraph wGT3X-BT accelerometers on a hip and a wrist. Participants’ performances were video-recorded. Based on the video data, accelerometer data were annotated with behavior labels to examine accelerometry signal outputs while performing the nine types of behaviors. Accelerometer data collected during 664 behavior assessments from the 21 participants were used for analysis. Hip vertical axis counts for walking were low (median = 49 counts/5 s). They were significantly lower than those recorded while a toddler was “carried” by an adult (median = 144 counts/5 s; p < 0.01). While standing, sitting, and riding in a stroller, very low hip vertical axis counts were registered (median ≤ 5 counts/5 s). Although wrist vertical axis and vector magnitude counts for “carried” were not higher than those for walking, they were higher than the cut-points for sedentary behaviors. Using various accelerometry signal features, machine learning techniques showed 89% accuracy to differentiate the “carried” behavior from ambulatory movements such as running, walking, crawling, and climbing. In conclusion, hip vertical axis counts alone may be unable to capture walking as physical activity and “carried” as sedentary behavior among toddlers. Machine learning techniques that utilize additional accelerometry signal features could help to recognize behavior types, especially to differentiate being “carried” from ambulatory movements. MDPI 2019-07-21 2019-07 /pmc/articles/PMC6678133/ /pubmed/31330889 http://dx.doi.org/10.3390/ijerph16142598 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kwon, Soyang
Zavos, Patricia
Nickele, Katherine
Sugianto, Albert
Albert, Mark V.
Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities
title Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities
title_full Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities
title_fullStr Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities
title_full_unstemmed Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities
title_short Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities
title_sort hip and wrist-worn accelerometer data analysis for toddler activities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678133/
https://www.ncbi.nlm.nih.gov/pubmed/31330889
http://dx.doi.org/10.3390/ijerph16142598
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