GGIR package - RDocumentation

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Getting started:

The package vignette and this short tutorial video provide an introduction to GGIR, including: How it can be installed, Key software features, and where to get help.

Contribution guidelines:

We always welcome contributions to the package. If you want to contribute to the development of GGIR, have a look at the contribution guidelines.

Images usaged

The copyright of the GGIR logo as contained in the file vignettes/GGIR-MASTERLOGO-RGB.png lies with Accelting (Almere, The Netherlands), please contact v.vanhees@accelting.com to ask for permission to use this logo.

All other images in this repository are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

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Version

Install

install.packages('GGIR')

Monthly Downloads

2,764

Version

3.0-0

License

Apache License (== 2.0) | file LICENSE

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/wadpac/GGIR/

Homepage

https://groups.google.com/forum/#!forum/RpackageGGIR

Maintainer

Vincent T van Hees

Last Published

October 16th, 2023

Functions in GGIR (3.0-0)

POSIXtime2iso8601

Convert POSIX to iso8601 timestamp

applyCosinorAnalyses

Apply Cosinor Analyses to time series

Heuristic algorithms for sustiained inactivty bouts detection

Append GGIR milestone data from neighbouring or overlapping recordings

A package to process multi-day raw accelerometer data

convertEpochData

convert external Epoch data to GGIR part 1 milestone data format

ShellDoc2Vignette

Extract Definition from Shell Documentation

applyExtFunction

Apply external function to acceleration data.

Shell function for analysing an accelerometer dataset.

Example output from g.calibrate

createConfigFile

Creates Config File based on variables in function GGIR environment

Check default parameters

cosinorAnalyses

Apply cosinor anlaysis and extended cosinor analysis

correctOlderMilestoneData

Corrects milestone data from g.part1 generated in older GGIR versions

Heuristic Algorithms estimating SPT window.

CalcSleepRegularityIndex

Calculates Sleep Regularity Index

Checks myfun object before it is passed to applyExtfunction

Generates vector of file names out of datadir input argument

Example output from g.getmeta

data.inspectfile

Example output from g.inspectfile

g.abr.day.names

Abbreviates daynames to numbers, needed for report generation in g.plot5

Function to analsyse meta-data generated by g.getmeta and g.impute

Function supports g.analyse. Not intended for direct use by user.

create_test_sleeplog_csv

Creates csv sleeplog file for testing purposes

detect_nonwear_clipping

Detect non-wear and clipping time in the raw accelerometer data

create_test_acc_csv

Creates csv data file for testing purposes

function to estimate calibration error and make recommendation for addressing it

Function to read activity log and make it useful for the rest of GGIR.

Extract ID from file header object

Extract metrics from acceleration signals

g.analyse.perfile

Function supports g.analyse. Not intended for direct use by user.

Extract parameters from input and add them to params

g.create.sp.mat

Converts sleep period information. Not intended for direct use

g.fragmentation

Fragmentation metrics from time series.

g.convert.part2.long

Convert part 2 report to long format

Calculates IV and IS

Extract M5 and L5 from time series

Downsample a vector of numeric values at three time resolutions

g.extractheadervars

Extracts header variables from header object

function to calculate bouts from vector of binary classes

g.intensitygradient

Intensity gradient calculation

Load and clean sleeplog information

g.detecmidnight

Detect all midnights in a time series

Assesses whether decimals in fileheader are stored with comma or dot separated decimals

g.analyse.perday

Function supports g.analyse. Not intended for direct use by user.

g.imputeTimegaps

Impute gaps in three axis raw accelerometer data

function to load and pre-process acceleration files

g.part5.analyseRest

Analyse rest (internal function)

function to inspect accelerometer file for brand, sample frequency and header

Function to extract meta-data (features) from data in accelerometer file

function to analyse and summarize pre-processed output from g.part1

g.part5.addfirstwake

Adds first wake if it is missing in part 4 output.

Adds the sustained inactivity bout to the ts series.

Function to identify invalid periods in the meta-data as generated by g.getmeta and to impute these invalid periods with the average of similar timepoints on other days of the measurement

g.part5.classifyNaps

Classify Naps from identified sustained inactivty bouts

g.part5.onsetwaketiming

Identify wake and sleepperiod window timing

Extract start time of a measurement

g.part5.lux_persegment

Extract key lux variables per segment of the data.

g.part5.savetimeseries

Saves oart 5 time series to csv files

g.part5.handle_lux_extremes

Check lux values for extremes and imputes or removes them

g.part5_initialise_ts

Initialise time series data from for part 5

Merge output from physical activity and sleep analysis into one report

g.part4_extractid

Extracts ID from filename and finds matching rows in sleeplog

Detection of sustained inactivity periods as needed for sleep detection in g.part4.

g.part5.wakesleepwindows

Label wake and sleepperiod window

function to generate a plot for quality check purposes

Generate report from milestone data produced by g.part2

g.readtemp_movisens

Reads the temperature from movisens files.

Create plot of sustained inactivity bouts

g.part5.fixmissingnight

Fix missing night in part 4 output

g.part5.definedays

Fix missing night in part 4 output

sustiained inactivty bouts detection

Check whether character timestamp is in iso8601 format.

Generate user-friendly visual report. The first part of the report summarizes important daily metrics in bar plot format. The second part of the report shows the raw data and annotations in 24-hr periods. Angle-z is shown with sleep annotations during the SPT (sleep period time) window. ENMO is shown with daytime inactivity and PA (physical activity) annotations in the lower section of each 24-hr plot. The PA annotations are based on a 10 minute bout metric and 80 of a 10 minute bout of MVPA. Vigorous PA is a short window of time above threshold.vig that is part of a bout of MVPA. Light PA is a short window of time above threshold.lig that is part of a bout of light PA.

is_this_a_dst_night

Check whether the night starting on a calendar date has DST.

get_starttime_weekday_meantemp_truncdata

Get starttime (adjusted), weekday, mean temp, and adjust data accordingly.

Generic functiont to read large blocks of accelerometer data

g.part5_analyseSegment

Analyses the time series per time segment for part 5

get_nw_clip_block_params

Set monitor brand specific parameters

Wrapper function around function GGIR

Labels detected sustained inactivity periods by g.part3 as either part of the Sleep Period Time window or not

Generate report from milestone data produced by g.part4

sustiained inactivty bouts detection

Generate report from milestone data produced by g.part5

Checks whether datadir is a directory or a vector with filenames

getfolderstructure

Extracts folderstructure based on data directory.

parametersVignette

Builds Section for Parameters Vignette

iso8601chartime2POSIX

Convert iso8601 timestamps to POSIX timestamp

Load default parameters

Read custom csv files with accelerometer data

Checks whether the files to process are collected with movisens accelerometers.

identify_levels

Identifies levels of behaviour for g.part5 function.

Round numeric columns and replace NA/NaN values by blank

Generate sustiained inactivty bouts report

updateBlocksize

Update blocksize of data to be read depending on available memory.

Detects whether accelerometer is worn