g.calibrate {GGIR}

function to estimate calibration error and make recommendation for addressing it

Description

Function starts by identifying ten second windows of non-movement. Next, the average acceleration per axis per window is used to estimate calibration error (offset and scaling) per axis. The function provides recommended correction factors to address the calibration error and a summary of the callibration procedure.

Usage

  g.calibrate(datafile, params_rawdata = c(), params_general = c(),
              params_cleaning = c(), inspectfileobject = c(), verbose = TRUE, ...)

Arguments

datafile

Name of accelerometer file

params_rawdata

See g.part1

params_general

See g.part1

params_cleaning

See g.part1

inspectfileobject

Output from the function g.inspectfile.

verbose

Boolean (default = TRUE). to indicate whether console message should be printed. Note that warnings and error are always printed and can be suppressed with suppressWarning() or suppressMessages().

...

Any argument used in the previous version of g.calibrate, which will now be used to overrule the arguments specified with the parameter objects.

Value

scale

scaling correction values, e.g. c(1,1,1)

offset

offset correction values, e.g. c(0,0,0)

tempoffset

correction values related to temperature, e.g. c(0,0,0)

cal.error.start

absolute difference between Euclidean norm during all non-movement windows and 1 g before autocalibration

cal.error.end

absolute difference between Euclidean norm during all non-movement windows and 1 g after autocalibration

spheredata

average, standard deviation, Euclidean norm and temperature (if available) for all ten second non-movement windows as used for the autocalibration procedure

npoints

number of 10 second no-movement windows used to populate the sphere

nhoursused

number of hours of measurement data scanned to find the ten second time windows with no movement

meantempcal

mean temperature corresponding to the data as used for autocalibration. Only applies to data where temperate data is collected and available to GGIR, such as GENEActiv, Axivity, and in some instances ad-hoc .csv data.

Author(s)

Vincent T van Hees <[e-mail]> Zhou Fang

References

• van Hees VT, Fang Z, Langford J, Assah F, Mohammad A, da Silva IC, Trenell MI, White T, Wareham NJ, Brage S. Auto-calibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol (1985). 2014 Aug 7

Examples

  ## Not run: 
    datafile = "C:/myfolder/testfile.bin"
    
    #Apply autocalibration:
    C = g.calibrate(datafile)
    print(C$scale)
    print(C$offset)
  
## End(Not run)