GGIR: Raw Accelerometer Data Analysis

A tool to process and analyse data collected with wearable raw acceleration sensors as described in Migueles and colleagues (JMPB 2019), and van Hees and colleagues (JApplPhysiol 2014; PLoSONE 2015). The package has been developed and tested for binary data from 'GENEActiv' <https://activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' <https://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:	2.8-2
Depends:	stats, utils, R (≥ 3.5.0)
Imports:	data.table, foreach, doParallel, signal, zoo, GENEAread, tuneR, unisensR, ineq, read.gt3x, ActCR, methods, GGIRread
Suggests:	testthat, covr, knitr, rmarkdown, actilifecounts
Published:	2022-10-06
Author:	Vincent T van Hees [aut, cre], Jairo H Migueles [aut], Severine Sabia [ctb], Matthew R Patterson [ctb], Zhou Fang [ctb], Joe Heywood [ctb], Joan Capdevila Pujol [ctb], Lena Kushleyeva [ctb], Mathilde Chen [ctb], Manasa Yerramalla [ctb], Patrick Bos [ctb], Taren Sanders [ctb], Medical Research Council UK [cph, fnd], Accelting [cph, fnd], French National Research Agency [cph, fnd]
Maintainer:	Vincent T van Hees <v.vanhees at accelting.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:	no
Citation:	GGIR citation info
Materials:	README NEWS
In views:	Tracking
CRAN checks:	GGIR results

Documentation:

Reference manual:	GGIR.pdf
Vignettes:	Published cut-points and how to use them in GGIR Embedding external functions in GGIR Accelerometer data processing with GGIR GGIR configuration parameters Day segment analyses with GGIR Reading csv files with raw data in GGIR

Downloads:

Package source:	GGIR_2.8-2.tar.gz
Windows binaries:	r-devel: GGIR_2.8-2.zip, r-release: GGIR_2.8-2.zip, r-oldrel: GGIR_2.8-2.zip
macOS binaries:	r-release (arm64): GGIR_2.8-2.tgz, r-oldrel (arm64): GGIR_2.8-2.tgz, r-release (x86_64): GGIR_2.8-2.tgz, r-oldrel (x86_64): GGIR_2.8-2.tgz
Old sources:	GGIR archive

Reverse dependencies:

Reverse imports:

mMARCH.AC, postGGIR

Linking:

Please use the canonical form https://CRAN.R-project.org/package=GGIR to link to this page.