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)