GGIR

Converts raw data from wearables into insightful reports for researchers investigating human daily physical activity and sleep.

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7
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601 commits | Last update: September 04, 2018

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What GGIR can do for you

  • GGIR is an R-package to process and analysis multi-day data collected with wearable raw data accelerometers for physical activity and sleep research.
  • GGIR uses this information to describe the data per day of measurement or per measurement, including estimates of physical activity, inactivity, and sleep. As part of the pipeline GGIR performs automatic signal calibration, detection of sustained abnormally high values, detection of sensor non-wear and calculation of average magnitude acceleration based on a variety of metrics.
  • GGIR is the only open source licensed software that provides a full pipeline for both physical activity and sleep analyses, with a high freedom for the user to configure the analyses to their needs.
  • The package has been used for domain science in 50+ publications, and is supported by 8 methodological publications.

The package has been developed and tested for binary data from GENEActiv and GENEA devices, .csv-export data from Actigraph devices, and .cwa and .wav-format data from Axivity. These devices are currently widely used in research on human daily physical activity.

A list of publications using GGIR can be found here: https://github.com/wadpac/GGIR/wiki/Publication-list

The package vignette which gives a general introduction can be found here: https://cran.r-project.org/web/packages/GGIR/vignettes/GGIR.html.

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Tags
  • Big data
Programming Language
  • R
License
  • LGPL-2.0

Participating organizations

Mentions

68 Journal articles

Thank you @vtvanhees for your work and support on the #GGIRpackage
– Damien Bachasson , Institute of Myology, Paris

Contributors

  • Jing Hua Zhao
    MRC Epidemiology Unit
  • Zhou Fang
    Activinsights Ltd
  • Joe Heywood
    University College London
  • Evgeny Mirkes
    University of Leicester
  • Séverine Sabia
    Inserm
  • Jairo Migueles
    University of Granada
  • Vincent van Hees
    Netherlands eScience Center
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Contact person
Vincent van Hees
Netherlands eScience Center