Cargando…
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...
Autores principales: | , , , , , , |
---|---|
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 |
_version_ | 1783628273946722304 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7764508 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT daviesalyse feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata AT allmanfarinellimargaret feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata AT owenkatherine feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata AT signallouise feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata AT hoskingcameron feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata AT wangleanne feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata AT baumanadrian feasibilitystudycomparingphysicalactivityclassificationsfromaccelerometerswithwearablecameradata |