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Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data

Device-based assessments are frequently used to measure physical activity (PA) but contextual measures are often lacking. There is a need for new methods, and one under-explored option is the use of wearable cameras. This study tested the use of wearable cameras in PA measurement by comparing intens...

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Autores principales: Davies, Alyse, Allman-Farinelli, Margaret, Owen, Katherine, Signal, Louise, Hosking, Cameron, Wang, Leanne, Bauman, Adrian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7764508/
https://www.ncbi.nlm.nih.gov/pubmed/33322117
http://dx.doi.org/10.3390/ijerph17249323
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author Davies, Alyse
Allman-Farinelli, Margaret
Owen, Katherine
Signal, Louise
Hosking, Cameron
Wang, Leanne
Bauman, Adrian
author_facet Davies, Alyse
Allman-Farinelli, Margaret
Owen, Katherine
Signal, Louise
Hosking, Cameron
Wang, Leanne
Bauman, Adrian
author_sort Davies, Alyse
collection PubMed
description Device-based assessments are frequently used to measure physical activity (PA) but contextual measures are often lacking. There is a need for new methods, and one under-explored option is the use of wearable cameras. This study tested the use of wearable cameras in PA measurement by comparing intensity classifications from accelerometers with wearable camera data. Seventy-eight 18–30-year-olds wore an Actigraph GT9X link accelerometer and Autographer wearable camera for three consecutive days. An image coding schedule was designed to assess activity categories and activity sub-categories defined by the 2011 Compendium of Physical Activities (Compendium). Accelerometer hourly detailed files processed using the Montoye (2020) cut-points were linked to camera data using date and time stamps. Agreement was examined using equivalence testing, intraclass correlation coefficient (ICC) and Spearman’s correlation coefficient (rho). Fifty-three participants contributing 636 person-hours were included. Reliability was moderate to good for sedentary behavior (rho = 0.77), light intensity activities (rho = 0.59) and moderate-to-vigorous physical activity (MVPA) (rho = 0.51). The estimates of sedentary behavior, light activity and MVPA from the two methods were similar, but not equivalent. Wearable cameras are a potential complementary tool for PA measurement, but practical challenges and limitations exist. While wearable cameras may not be feasible for use in large scale studies, they may be feasible in small scale studies where context is important.
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spelling pubmed-77645082020-12-27 Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data Davies, Alyse Allman-Farinelli, Margaret Owen, Katherine Signal, Louise Hosking, Cameron Wang, Leanne Bauman, Adrian Int J Environ Res Public Health Article Device-based assessments are frequently used to measure physical activity (PA) but contextual measures are often lacking. There is a need for new methods, and one under-explored option is the use of wearable cameras. This study tested the use of wearable cameras in PA measurement by comparing intensity classifications from accelerometers with wearable camera data. Seventy-eight 18–30-year-olds wore an Actigraph GT9X link accelerometer and Autographer wearable camera for three consecutive days. An image coding schedule was designed to assess activity categories and activity sub-categories defined by the 2011 Compendium of Physical Activities (Compendium). Accelerometer hourly detailed files processed using the Montoye (2020) cut-points were linked to camera data using date and time stamps. Agreement was examined using equivalence testing, intraclass correlation coefficient (ICC) and Spearman’s correlation coefficient (rho). Fifty-three participants contributing 636 person-hours were included. Reliability was moderate to good for sedentary behavior (rho = 0.77), light intensity activities (rho = 0.59) and moderate-to-vigorous physical activity (MVPA) (rho = 0.51). The estimates of sedentary behavior, light activity and MVPA from the two methods were similar, but not equivalent. Wearable cameras are a potential complementary tool for PA measurement, but practical challenges and limitations exist. While wearable cameras may not be feasible for use in large scale studies, they may be feasible in small scale studies where context is important. MDPI 2020-12-13 2020-12 /pmc/articles/PMC7764508/ /pubmed/33322117 http://dx.doi.org/10.3390/ijerph17249323 Text en © 2020 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
Davies, Alyse
Allman-Farinelli, Margaret
Owen, Katherine
Signal, Louise
Hosking, Cameron
Wang, Leanne
Bauman, Adrian
Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data
title Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data
title_full Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data
title_fullStr Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data
title_full_unstemmed Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data
title_short Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data
title_sort feasibility study comparing physical activity classifications from accelerometers with wearable camera data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7764508/
https://www.ncbi.nlm.nih.gov/pubmed/33322117
http://dx.doi.org/10.3390/ijerph17249323
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