Process Count Data

Usage

acti_calculate_counts(
  data,
  epoch = 60L,
  resample = TRUE,
  lfe_select = FALSE,
  verbose = TRUE
)

acti_calculate_wear(
  data,
  method = c("choi", "troiano"),
  use_magnitude = TRUE,
  ...
)

acti_calculate_nonwear(
  data,
  method = c("choi", "troiano"),
  use_magnitude = TRUE,
  ...
)

acti_apply_cole_kripke(data)

acti_apply_tudor_locke(data, ...)

acti_apply_sadeh(data, ...)

Arguments

data: A data.frame from acti_calculate_counts that has columns axis1-3 and counts
epoch: epoch length in seconds. Default is 60 seconds. See agcounts::calculate_counts()
resample: (recommended) resample the data to 30Hz using actibase::resample vs. using the resampling method from agcounts::calculate_counts.
lfe_select: Apply the Actigraph Low Frequency Extension filter. See agcounts::calculate_counts() higher values are higher levels of verbosity.
verbose: print diagnostic messages. Either logical or integer, where
method: Method for detecting non-wear, either "choi" or "troiano", corresponding to actigraph.sleepr::apply_choi() or actigraph.sleepr::apply_troiano()
use_magnitude: If TRUE, the magnitude of the vector (axis1, axis2, axis3) is used to measure activity; otherwise the axis1 value is used.
...: additional arguments to pass to actigraph.sleepr function

Value

A data.frame of transformed data

Note

This calls the downstream wear-processing helpers used by actigraph.sleepr

Examples

if (FALSE) { # \dontrun{
path = actiread::acti_example_gt3x()
ac = actiread::acti_read_gt3x(path)
out = acti_calculate_counts(ac)
} # }
data = actimetrics::acti_count_data
wear = actimetrics::acti_calculate_wear(data)
tro_wear = actimetrics::acti_calculate_wear(data, method = "troiano")
ck = actimetrics::acti_apply_cole_kripke(data)
tl = actimetrics::acti_apply_tudor_locke(ck)
sadeh = actimetrics::acti_apply_sadeh(ck)