GGIR (version 2.6-0)

GGIR-package: A package to process multi-day raw accelerometer data

Description

Disclaimer: If you are a new GGIR user then please see package vignette for an introduction to GGIR.

This document is primarily aimed at documenting the functions and their input arguments.

Please note that there is google discussion group for this package (link below).

You can thank us for sharing the code in this package and for developing it as a generic purpose tool by citing the package name and by citing the supporting publications (e.g. Migueles et al. 2019) in your publications.

Details

Package:	GGIR
Type:	Package
Version:	2.6-0
Date:	2022-02-02
License:	LGPL (>= 2.0, < 3)
Discussion group:	https://groups.google.com/forum/#!forum/rpackageggir

References

• Migueles JH, Rowlands AV, et al. GGIR: A Research Community-Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data. Journal for the Measurement of Physical Behaviour. 2(3) 2019. doi:10.1123/jmpb.2018-0063.

• van Hees VT, Gorzelniak L, Dean Leon EC, Eder M, Pias M, et al. (2013) Separating Movement and Gravity Components in an Acceleration Signal and Implications for the Assessment of Human Daily Physical Activity. PLoS ONE 8(4): e61691. doi:10.1371/journal.pone.0061691

• van Hees VT, Fang Z, Langford J, Assah F, Mohammad A, da Silva IC, Trenell MI, White T, Wareham NJ, Brage S. Auto-calibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol (1985). 2014 Aug 7

• van Hees VT, Sabia S, et al. (2015) A novel, open access method to assess sleep duration using a wrist-worn accelerometer, PLoS ONE, November 2015

Examples

# NOT RUN {
  
# }
# NOT RUN {
    #inspect file:
    I = g.inspectfile(datafile)

    #autocalibration:
    C = g.calibrate(datafile)

    #get meta-data:
    M = g.getmeta(datafile)
  
# }
# NOT RUN {
  data(data.getmeta)
  data(data.inspectfile)
  data(data.calibrate)

  #impute meta-data:
  IMP = g.impute(M = data.getmeta, I = data.inspectfile)
  #analyse and produce summary:
  A = g.analyse(I = data.inspectfile, C = data.calibrate, M = data.getmeta, IMP)
  #plot data
  g.plot(IMP, M = data.getmeta, I = data.inspectfile, durplot=4)
# }