Accelerometry Data in Health Research: Challenges and Opportunities

Marta Karas (), Jiawei Bai, Marcin Strączkiewicz, Jaroslaw Harezlak, Nancy W. Glynn, Tamara Harris, Vadim Zipunnikov, Ciprian Crainiceanu and Jacek K. Urbanek ()
Additional contact information
Marta Karas: Johns Hopkins University
Jiawei Bai: Johns Hopkins University
Marcin Strączkiewicz: Indiana University Bloomington
Jaroslaw Harezlak: Indiana University Bloomington
Nancy W. Glynn: University of Pittsburgh
Tamara Harris: National Institute on Aging
Vadim Zipunnikov: Johns Hopkins University
Ciprian Crainiceanu: Johns Hopkins University
Jacek K. Urbanek: Johns Hopkins University

Statistics in Biosciences, 2019, vol. 11, issue 2, No 2, 210-237

Abstract: 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.

Keywords: Wearable computing; Accelerometry; Wearable accelerometers; Physical activity; Accelerometers (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s12561-018-9227-2

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