Package: GGIR
Type: Package
Title: Raw Accelerometer Data Analysis
Version: 1.9-0
Date: 2019-03-14
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"))
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.
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: MASS, signal, zoo, mmap, bitops, matlab, GENEAread, tuneR,
        testthat, covr, knitr, rmarkdown
Imports: data.table, Rcpp (>= 0.12.10)
Depends: stats, utils, R (>= 3.1.2)
NeedsCompilation: yes
LinkingTo: Rcpp
VignetteBuilder: knitr
ByteCompile: yes
Packaged: 2019-03-14 22:28:55 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]
Repository: CRAN
Date/Publication: 2019-03-15 07:03:34 UTC
Built: R 3.4.4; x86_64-w64-mingw32; 2019-04-25 19:17:07 UTC; windows
Archs: i386, x64
