Citation

Karas M, Bai J, Strączkiewicz M, Harezlak J, Glynn NW, Harris T, Zipunnikov V, Crainiceanu C, Urbanek JK. Stat. Biosci. 2019; 11(2): 210-237.

Affiliation

Center on Aging and Health, Division of Geriatric Medicine and Gerontology, Department of Medicine, School of Medicine, Johns Hopkins University, jurbane2@jhu.edu.

Copyright

(Copyright © 2019, International Chinese Statistical Association, Publisher Springer Science+Business Media)

DOI

10.1007/s12561-018-9227-2

PMID

31762829

PMCID

PMC6874221

Abstract

Wearable accelerometers provide detailed, objective, and continuous measurements of physical activity (PA). Recent advances in technology and the decreasing cost of wearable devices led to an explosion in the popularity of wearable technology in health research. An ever-increasing number of studies collect high-throughput, sub-second level raw acceleration data. In this paper, we discuss problems related to the collection and analysis of raw accelerometry data and refer to published solutions. In particular, we describe the size and complexity of the data, the within- and between-subject variability, and the effects of sensor location on the body. We also discuss challenges related to sampling frequency, device calibration, data labeling and multiple PA monitors synchronization. We illustrate these points using the Developmental Epidemiological Cohort Study (DECOS), which collected raw accelerometry data on individuals both in a controlled and the free-living environment.

Language: en

Keywords

Accelerometers; Accelerometry; Physical activity; Wearable accelerometers; Wearable computing