Package: GGIR
Type: Package
Title: Raw Accelerometer Data Analysis
Version: 1.11-0
Date: 2019-12-03
Authors@R: c(person("Vincent T","van Hees",role=c("aut","cre"),
                  email="vincentvanhees@gmail.com"),
                  person("Zhou","Fang",role="ctb"),
                  person("Jing Hua","Zhao",role="ctb"),
                  person("Joe","Heywood",role="ctb"),
                  person("Evgeny","Mirkes",role="ctb"),
                  person("Severine","Sabia",role="ctb"),
                  person("Joan","Capdevila Pujol",role="ctb"),
                  person("Jairo H","Migueles",role="ctb"),
                  person("Matthew R","Patterson",role="ctb"))
Maintainer: Vincent T van Hees <vincentvanhees@gmail.com>
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in 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/product/ax3>. 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.
URL: https://github.com/wadpac/GGIR/,
        https://groups.google.com/forum/#!forum/RpackageGGIR
BugReports: https://github.com/wadpac/GGIR/issues
License: LGPL (>= 2.0, < 3) | file LICENSE
Suggests: testthat, covr, knitr, rmarkdown
Imports: data.table, Rcpp (>= 0.12.10), foreach, doParallel, signal,
        zoo, bitops, matlab, GENEAread, tuneR
Depends: stats, utils, R (>= 3.5.0)
NeedsCompilation: yes
LinkingTo: Rcpp
VignetteBuilder: knitr
ByteCompile: yes
Packaged: 2019-12-03 19:38:28 UTC; vincent
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]
Repository: CRAN
Date/Publication: 2019-12-04 07:50:10 UTC
Built: R 4.0.0; x86_64-w64-mingw32; 2020-04-10 07:29:33 UTC; windows
Archs: i386, x64
