Package: GGIR 3.1-4
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/>, binary (.gt3x) and .csv-export data from 'Actigraph' <https://theactigraph.com> devices, and binary (.cwa) and .csv-export 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. Also the package allows for external function embedding.
Authors:
GGIR_3.1-4.tar.gz
GGIR_3.1-4.zip(r-4.5)GGIR_3.1-4.zip(r-4.4)GGIR_3.1-4.zip(r-4.3)
GGIR_3.1-4.tgz(r-4.4-any)GGIR_3.1-4.tgz(r-4.3-any)
GGIR_3.1-4.tar.gz(r-4.5-noble)GGIR_3.1-4.tar.gz(r-4.4-noble)
GGIR_3.1-4.tgz(r-4.4-emscripten)GGIR_3.1-4.tgz(r-4.3-emscripten)
GGIR.pdf |GGIR.html✨
GGIR/json (API)
NEWS
# Install 'GGIR' in R: |
install.packages('GGIR', repos = c('https://wadpac.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/wadpac/ggir/issues
- data.calibrate - Example output from g.calibrate
- data.getmeta - Example output from g.getmeta
- data.inspectfile - Example output from g.inspectfile
- data.metalong - Metalong object as part of part 1 milestone data
- data.ts - Time series data.frame stored by part 5
accelerometeractivity-recognitioncircadian-rhythmmovement-sensorsleep
Last updated 1 hours agofrom:90c4b3ade3. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-win | OK | Nov 06 2024 |
R-4.5-linux | OK | Nov 06 2024 |
R-4.4-win | OK | Nov 06 2024 |
R-4.4-mac | OK | Nov 06 2024 |
R-4.3-win | OK | Nov 06 2024 |
R-4.3-mac | OK | Nov 06 2024 |
Exports:appendRecordsapplyCosinorAnalysesCalcSleepRegularityIndexcheck_logcheck_paramsconvertEpochDatacorrectOlderMilestoneDatacosinorAnalysescreateConfigFiledatadir2fnamesdetect_nonwear_clippingextract_paramsextractIDg.abr.day.namesg.analyseg.applymetricsg.calibrateg.conv.actlogg.create.sp.matg.detecmidnightg.dotorcommag.extractheadervarsg.fragmentationg.getboutg.getM5L5g.getmetag.getstarttimeg.imputeg.imputeTimegapsg.inspectfileg.intensitygradientg.IVISg.loadlogg.part1g.part2g.part3g.part4g.part4_extractidg.part5g.part5_analyseSegmentg.part5_initialise_tsg.part5.addfirstwakeg.part5.addsibg.part5.analyseRestg.part5.classifyNapsg.part5.definedaysg.part5.fixmissingnightg.part5.handle_lux_extremesg.part5.lux_persegmentg.part5.onsetwaketimingg.part5.savetimeseriesg.part5.wakesleepwindowsg.part6g.plotg.plot5g.readaccfileg.readtemp_movisensg.report.part2g.report.part4g.report.part5g.report.part5_dictionaryg.report.part6g.shell.GGIRg.sib.detg.sib.plotg.sib.sumg.sibreportg.weardecget_nw_clip_block_paramsget_starttime_weekday_truncdataGGIRHASIBHASPTidentify_levelsis_this_a_dst_nightis.ISO8601isfilelistismovisensiso8601chartime2POSIXload_paramsparametersVignettepart6AlignIndividualspart6PairwiseAggregationPOSIXtime2iso8601read.myacc.csvShellDoc2Vignettetidyup_dfupdateBlocksize
Dependencies:ActCRbackportsbase64encbitbit64bitopsbslibcachemcellrangercheckmatecliclustercodetoolscolorspacecommonmarkcosinorcosinor2cowplotcpp11crayondata.tabledigestdoParalleldplyrevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsgenericsGGIRreadggplot2glueGPArotationgridExtragtablehexViewhighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvineqirrisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelifecyclelpSolvelubridatemagrittrMASSmatlabMatrixmatrixStatsmemoisemgcvmimeminpack.lmmnormtmunsellnlmennetpillarpkgconfigprettyunitsprogresspromisespsychpurrrR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppread.gt3xreadxlrematchrlangrmarkdownrpartrstudioapisassscalesshinysignalsourcetoolsstringistringrtibbletidyselecttimechangetinytextzdbunisensRutf8vctrsviridisviridisLitevroomwithrxfunXMLxtableyamlzoo
Accelerometer data processing with GGIR
Rendered fromGGIR.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-09-03
Started: 2017-04-28
Day segment analyses with GGIR
Rendered fromTutorialDaySegmentAnalyses.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-09-03
Started: 2021-10-20
Embedding external functions in GGIR
Rendered fromExternalFunction.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-06-28
Started: 2020-04-30
GGIR configuration parameters
Rendered fromGGIRParameters.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-09-23
Started: 2022-09-19
GGIR output
Rendered fromGGIRoutput.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-09-03
Started: 2024-06-13
Published cut-points and how to use them in GGIR
Rendered fromCutPoints.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-09-03
Started: 2022-09-19
Reading csv files with raw data in GGIR
Rendered fromreadmyacccsv.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2024-10-04
Started: 2022-05-05