A Review of Statistical Analyses on Physical Activity Data Collected from Accelerometers. Academic Article

abstract

• Studies for the associations between physical activity and disease risk have been supported by newly developed wearable accelerometer-based devices. These devices record raw activity/movement information in real time on a second-by-second basis and the data can be converted to a variety of summary metrics, such as energy expenditure, sedentary time and moderate-vigorous intensity physical activity. Here we review some of the methods used to analyze the accelerometer data and the R packages that can generate activity related variables from raw data. We also discuss longitudinal data and functional data approaches to perform analyses for various research purposes.

authors

• Carroll, Raymond

published proceedings

• Stat Biosci

author list (cited authors)

• Zhang, Y., Li, H., Keadle, S. K., Matthews, C. E., & Carroll, R. J.

citation count

• 3

complete list of authors

• Zhang, Yukun||Li, Haocheng||Keadle, Sarah Kozey||Matthews, Charles E||Carroll, Raymond J

publication date

• July 2019

publisher

• Springer Nature  Publisher

published in

• Statistics in Biosciences  Journal

keywords

• Accelerometer
• Functional Data Analysis
• Longitudinal Data Analysis
• Physical Activity
• R Package

PubMed Central ID

• 32863980

Digital Object Identifier (DOI)

• 10.1007/s12561-019-09250-6

start page

• 465

end page

• 476

volume

• 11

issue

• 2

URL

• http://dx.doi.org/10.1007/s12561-019-09250-6