GGIR

Vincent van Hees

doi:10.5281/zenodo.1051064

GGIR

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

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Cite this software

DOI:

10.5281/zenodo.1051064

Description

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 70+ 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.

Keywords

Big data

Programming language

R 100%

License

LGPL-2.0

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Packages

Participating organisations

Life Sciences

Reference papers

1.
Author(s): Jairo H. Migueles, Alex V. Rowlands, Florian Huber, Séverine Sabia, Vincent T. van Hees
Published in Journal for the Measurement of Physical Behaviour by Human Kinetics in 2019, page: 188-196
10.1123/jmpb.2018-0063

Mentions

1.
Published in 2019

1.
Author(s): Vincent T van Hees, Jairo H Migueles
Published in CRAN: Contributed Packages by The R Foundation in 2013
10.32614/cran.package.ggir

Testimonials

Thank you @vtvanhees for your work and support on the #GGIRpackage

– Damien Bachasson, Institute of Myology, Paris, France

The GGIR R package has been used extensively with GENEActiv, ActiGraph, and Axivity data and has grown organically to become the application of choice for many researchers using raw acceleration data to study not only PA and sedentary time, but also sleep.

– Prof. Stuart Fairclough, Edgehill University, Ormskirk, UK