Raw Accelerometer Data Analysis

A tool to process and analyse data collected with wearable raw acceleration sensors as described in van Hees and colleagues (2014) and (2015) . The package has been developed and tested for binary data from 'GENEActiv' < https://www.activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' < http://actigraphcorp.com> devices, and .cwa and .wav-format data from 'Axivity' < https://axivity.com/product/ax3>. These devices are currently widely used in research on human daily physical activity.

Build Status codecov DOI

The code in this repository is the development version for the code in R-package GGIR Contributions are welcome.

For developers:

We work with GitHub Flow branching model.

Key steps:

  1. Create your own working branch
  2. Make your changes in that branch
  3. Commit your changes to your working branch as long as you are not finished with your development
  4. Once your work is finished, make a pull request, such that another developer can review your changes before merging them with the master branch

For end-users unfamiliar with GitHub:

If you would like to propose additional functionalities or report an issue. Go to issues and create a new issue.

If you would like to propose changes to the text of the manual this is possible.

  1. Please go to the man folder which holds all the parts of the manual.
  2. Go to the part of the manual you want to edit and click on edit button (little pencil symbol) and make your changes.
  3. Once you are finished, scroll down and describe you update and select the radio button "Create a new branch for this commit and start a pull request". One of the developers will then be able to review your changes and merge them in the master version of the code.
  4. Click the green button "Propose file changes"


Reference manual

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1.5-17 by Vincent T van Hees, 4 days ago

https://github.com/wadpac/GGIR/, https://groups.google.com/forum/#!forum/RpackageGGIR

Report a bug at https://github.com/wadpac/GGIR/issues

Browse source code at https://github.com/cran/GGIR

Authors: Vincent T van Hees [aut, cre], Zhou Fang [ctb], Jing Hua Zhao [ctb], Joe Heywood [ctb], Evgeny Mirkes [ctb], Severine Sabia [ctb], Jairo H Migueles [ctb]

Documentation:   PDF Manual  

LGPL (>= 2.0, < 3) | file LICENSE license

Imports data.table, Rcpp

Depends on stats, utils

Suggests MASS, signal, zoo, mmap, bitops, matlab, GENEAread, tuneR, testthat, covr, knitr, rmarkdown

Linking to Rcpp

See at CRAN