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


  • 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.

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