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

Alyse Davies, Margaret Allman-Farinelli, Katherine Owen, Louise Signal, Cameron Hosking, Leanne Wang and Adrian Bauman
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Alyse Davies: Nutrition and Dietetics Group, Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Margaret Allman-Farinelli: Nutrition and Dietetics Group, Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Katherine Owen: Prevention Research Centre, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia
Louise Signal: Health Promotion & Policy Research Unit, Department of Public Health, University of Otago, P.O. Box 7343, Wellington South, Wellington 6242, New Zealand
Cameron Hosking: Transformational Bioinformatics Group, Commonwealth Scientific and Industrial Research Organization, North Ryde, Sydney, NSW 2113, Australia
Leanne Wang: Nutrition and Dietetics Group, Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Adrian Bauman: Prevention Research Centre, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia

IJERPH, 2020, vol. 17, issue 24, 1-13

Abstract: 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.

Keywords: methods; physical activity; compendium; wearable cameras; accelerometer; activity intensities; sedentary behavior; measurement; young adults; public health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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