GGIR: Raw Accelerometer Data Analysis

A tool to process and analyse data collected with wearable raw acceleration sensors as described in Migueles and colleagues (2019) <doi:10.1123/jmpb.2018-0063>, van Hees and colleagues (2014) <doi:10.1152/japplphysiol.00421.2014>, and (2015) <doi:10.1371/journal.pone.0142533>. 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>. These devices are currently widely used in research on human daily physical activity. Further, the package can handle accelerometer data file from any other sensor brand providing that the data is stored in csv format and has either no header or a two column header. Also the package allows for external function embedding.

Version: 2.0-0
Depends: stats, utils, R (≥ 3.5.0)
Imports: data.table, Rcpp (≥ 0.12.10), foreach, doParallel, signal, zoo, bitops, matlab, GENEAread, tuneR
LinkingTo: Rcpp
Suggests: testthat, covr, knitr, rmarkdown
Published: 2020-05-01
Author: Vincent T van Hees [aut, cre], Zhou Fang [ctb], Jing Hua Zhao [ctb], Joe Heywood [ctb], Evgeny Mirkes [ctb], Severine Sabia [ctb], Joan Capdevila Pujol [ctb], Jairo H Migueles [ctb], Matthew R Patterson [ctb], Dan Jackson [ctb]
Maintainer: Vincent T van Hees <vincentvanhees at gmail.com>
BugReports: https://github.com/wadpac/GGIR/issues
License: LGPL-2 | LGPL-2.1 | file LICENSE [expanded from: LGPL (≥ 2.0, < 3) | file LICENSE]
URL: https://github.com/wadpac/GGIR/, https://groups.google.com/forum/#!forum/RpackageGGIR
NeedsCompilation: yes
Citation: GGIR citation info
Materials: README NEWS
In views: Tracking
CRAN checks: GGIR results

Downloads:

Reference manual: GGIR.pdf
Vignettes: Embedding external functions in GGIR
Accelerometer data processing with GGIR
Package source: GGIR_2.0-0.tar.gz
Windows binaries: r-devel: GGIR_2.0-0.zip, r-release: GGIR_2.0-0.zip, r-oldrel: GGIR_2.0-0.zip
macOS binaries: r-release: GGIR_2.0-0.tgz, r-oldrel: GGIR_2.0-0.tgz
Old sources: GGIR archive

Reverse dependencies:

Reverse imports: AGread

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