Package {actimetrics}

Type: Package
Title: Create Metrics Actigraphy and Activity Analysis
Version: 0.4.0
Description: Provides functions for calibrating, counting, and summarizing actigraphy and activity data into specific metrics and sleep measures. The metrics include activity counts, step counts, activity index, Monitor Independent Movement Summary Unit (MIMS), mean amplitude deviation (MAD), and provides wrappers for sleep estimation from activity counts using Tudor-Locke (2014) <doi:10.1139/apnm-2013-0173> and Sadeh (1994) <doi:10.1093/sleep/17.3.201>.
License: GPL-3
Depends: R (≥ 4.1.0)
Suggests: testthat, utils, covr, knitr, httr, rmarkdown, MIMSunit, data.table, reticulate, stepcount (≥ 0.6.0), actigraph.sleepr (≥ 0.3.1), agcounts (≥ 0.6.7), callr
Encoding: UTF-8
VignetteBuilder: knitr
Imports: actibase, actiread, dplyr, lubridate, assertthat, purrr, tibble, rlang, stats, tidyr, walking (≥ 0.8.0), methods
LazyData: true
Config/roxygen2/version: 8.0.0
URL: https://jhuwit.github.io/actimetrics/
BugReports: https://github.com/jhuwit/actimetrics/issues
NeedsCompilation: no
Packaged: 2026-09-08 16:17:38 UTC; johnmuschelli
Author: John Muschelli ORCID iD [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:10:15 UTC

Process Count Data

Description

Process Count Data

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::acti_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

A data.frame of transformed data with columns axis1-3, counts, and counts_log10.

A data.frame of transformed data

Note

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

Examples



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)

Calculate Step Counts via Oak/Forest

Description

Calculate Step Counts via Oak/Forest

Usage

acti_calculate_forest(data, ...)

Arguments

data

A data.frame, AccData object, or GT3X file with X, Y, Z, and time

...

Additional arguments passed to walking::find_walking()

Value

A tibble with minute-level time, steps columns.

Examples


  Sys.setenv("SSQ_PARALLEL" = 0)
  if (reticulate::py_module_available("forest")) {
    data = actiread::acti_read_gt3x(actiread::acti_example_gt3x())
    steps = acti_calculate_forest(data, sample_rate = 100)
  }

Calculate Summary Measures from Raw Accelerometer Data

Description

Calculate Summary Measures from Raw Accelerometer Data

Usage

acti_calculate_measures(
  data,
  unit = "1 min",
  fix_zeros = TRUE,
  dynamic_range = NULL,
  calculate_mims = TRUE,
  calculate_ac = TRUE,
  flag_data = TRUE,
  flags = NULL,
  ensure_all_time = TRUE,
  verbose = TRUE,
  sample_rate = NULL,
  ...
)

acti_calculate_ai(
  data,
  unit = "1 min",
  ensure_all_time = TRUE,
  verbose = FALSE
)

acti_calculate_activity_index(
  data,
  unit = "1 min",
  ensure_all_time = TRUE,
  verbose = FALSE
)

acti_calculate_flags(data, unit = "1 min", ensure_all_time = TRUE)

acti_calculate_n_idle(data, unit = "1 min", ensure_all_time = TRUE)

acti_calculate_enmo(...)

acti_calculate_ai_defined(...)

acti_calculate_mad(
  data,
  unit = "1 min",
  ensure_all_time = TRUE,
  verbose = FALSE
)

acti_calculate_auc(
  data,
  unit = "1 min",
  sample_rate = NULL,
  allow_truncation = FALSE,
  ensure_all_time = TRUE,
  verbose = TRUE
)

acti_calculate_fast_mims(
  data,
  unit = "1 min",
  dynamic_range = NULL,
  sample_rate = NULL,
  allow_truncation = TRUE,
  ensure_all_time = TRUE,
  verbose = TRUE,
  ...
)

acti_calculate_mims(
  data,
  unit = "1 min",
  dynamic_range = c(-6, 6),
  ensure_all_time = TRUE,
  ...
)

Arguments

data

An object with columns X, Y, and Z or an object of class AccData

unit

length of time to calculate measures over. a character string specifying a time unit or a multiple of a unit to be rounded to. Valid base units are second, minute, hour, day, week, month, bimonth, quarter, season, halfyear, and year. Arbitrary unique English abbreviations as in the lubridate::period() constructor are allowed.

fix_zeros

Should actibase::acti_fill_zeros() be run before calculating the measures?

dynamic_range

Dynamic range of the device, in gravity units

calculate_mims

Should MIMS units be calculated?

calculate_ac

Should Activity Counts from the agcounts package be calculated?

flag_data

Should the downstream overlay flag_qc() be run? It will be executed after fix_zeros before any measure calculation

flags

the flags to calculate, passed to the downstream overlay flag_qc()

ensure_all_time

if TRUE, then all times from the first to last times will be in the output, even if data during that time was not in the input

verbose

print diagnostic messages

sample_rate

sample rate of data, if not specified in header of object

...

additional arguments to pass to MIMSunit::mims_unit()

allow_truncation

truncate small values

Value

A data set with the calculated features

Examples

file = actiread::acti_example_gt3x()
res = actiread::acti_read_gt3x(file, verbose = FALSE)
res = res[1:12000, ]
measures = acti_calculate_measures(
  res,
  dynamic_range = NULL,
  calculate_mims = FALSE,
  calculate_ac = FALSE,
  flag_data = FALSE
)
auc = acti_calculate_auc(res)

mims = acti_calculate_mims(res, dynamic_range = NULL)

if (requireNamespace("data.table", quietly = TRUE)) {
   dt = data.table::as.data.table(res)
   out = acti_calculate_measures(dt, calculate_mims = FALSE, flag_data = FALSE,
     calculate_ac = FALSE)
}

Calculate Step Counts via Oak/Forest

Description

Calculate Step Counts via Oak/Forest

Usage

acti_calculate_sdt(data, sample_rate = NULL, ...)

Arguments

data

A data.frame, AccData object, or GT3X file with X, Y, Z, and time

sample_rate

Sample rate in Hz. If omitted, it is taken from the input object when available.

...

Additional arguments passed to walking::sdt_count_steps()

Value

A tibble with minute-level time, steps columns.

Examples

data = actiread::acti_read_gt3x(actiread::acti_example_gt3x())
steps = acti_calculate_sdt(data)

Calculate Step Counts via stepcount

Description

Use the stepcount package to estimate steps from raw accelerometer data and summarize them to minute-level epochs (as opposed to 10s default)

Usage

acti_calculate_stepcount(data, sample_rate = NULL, ..., epoch = "1 minute")

Arguments

data

A data.frame, AccData object, or GT3X file with X, Y, Z, and time

sample_rate

Sample rate in Hz. If omitted, it is taken from the input object when available.

...

Additional arguments passed to stepcount::stepcount()

epoch

epoch unit to aggregate the data to, passed to lubridate::floor_date(), original output is at 10-seconds

Value

A tibble with minute-level time, steps, and walking columns.

Examples


  # reticulate::py_require("stepcount==3.11.0", python_version = "3.10", action = "add")
  # sc = try({ reticulate::import("stepcount") })
  if (stepcount::have_stepcount()) {
    data = actiread::acti_read_gt3x(actiread::acti_example_gt3x())
    steps = acti_calculate_stepcount(data, sample_rate = 100)
    steps = acti_calculate_stepcount(data, model_type = "rf")
  }

Calculate Step Counts via Verisense

Description

Calculate Step Counts via Verisense

Usage

acti_calculate_verisense(
  data,
  resample_to_15hz = TRUE,
  method = c("original", "revised"),
  ...
)

Arguments

data

A data.frame, AccData object, or GT3X file with X, Y, Z, and time

resample_to_15hz

resample data to 15Hz, passed to walking::estimate_steps_verisense()

method

parameters to estimate walking, either original or revised, passed to walking::estimate_steps_verisense()

...

Additional arguments passed to walking::estimate_steps_verisense()

Value

A tibble with minute-level time, steps columns.

Examples

data = actiread::acti_read_gt3x(actiread::acti_example_gt3x())
steps = acti_calculate_verisense(data)

Calibrate Accelerometer Data using agcounts

Description

This uses the van Hees calibration method typically exposed through GGIR, implemented here via agcounts::agcalibrate().

Usage

acti_calibrate(
  data,
  verbose = TRUE,
  fill_zeroes = TRUE,
  round_after_calibration = TRUE,
  ...
)

Arguments

data

Either a GT3X file, AccData object, or data.frame with X/Y/Z and time

verbose

print diagnostic messages, higher number result in higher verbosity

fill_zeroes

Should actibase::acti_fill_zeros() be run before calculating the measures? This trims zero values from the beginning and the end of the time course using last observation carried forward behavior.

round_after_calibration

Should the data be rounded after calibration? Will round to 3 digits

...

Additional arguments to pass to agcounts::agcalibrate()

Value

A calibrated dataset with the same columns as the input data, but with the X/Y/Z values calibrated using the van Hees method.

Examples


  res = acti_calibrate(data = actiread::acti_example_gt3x())

Example Actigraphy/Activity Count Data

Description

Example Actigraphy/Activity Count Data

Usage

acti_count_data

Format

A data.frame with the columns

time

time at the minute level

axis1

axis1 (Y) counts

axis2

axis2 (X) counts

axis3

axis3 (Z) counts

counts

vector magnitude of all 3 axes column

This data was taken from running agcounts::calculate_counts via acti_calculate_counts on actibase::acti_raw_data.

Process Count Data

Description

Process Count Data

Usage

acti_process(
  data,
  lfe_select = FALSE,
  method = c("choi", "troiano"),
  use_magnitude = TRUE,
  verbose = TRUE,
  ...
)

Arguments

data

A data.frame from acti_calculate_counts that has columns axis1-3 and counts

lfe_select

Apply the Actigraph Low Frequency Extension filter. See agcounts::calculate_counts() higher values are higher levels of verbosity.

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.

verbose

print diagnostic messages. Either logical or integer, where

...

additional arguments to pass to actigraph.sleepr function

Value

A data frame containing activity counts and wear-time indicators.

Note

For acti_process_gt3x, the ... argument are passed to actiread::acti_read_gt3x()

Default MIMS worker functions

Description

Default MIMS worker functions

Usage

mims_default_extrapolation(data, dynamic_range = NULL)

mims_default_interpolation(data)

mims_default_filtering(data)

Arguments

data

data set of data, usually time and X/Y/Z. Usually from actiread::acti_read_gt3x()

dynamic_range

dynamic range of the data. Will be passed to actibase::get_dynamic_range()

Value

A data set of data

Default MIMS Pre-processing

Description

Default MIMS Pre-processing

Usage

mims_default_processing(
  data,
  use_extrapolation = TRUE,
  use_filtering = TRUE,
  verbose = TRUE,
  dynamic_range = NULL,
  round_after_processing = FALSE
)

Arguments

data

Data set of raw accelerometry values, usually time and X/Y/Z. Usually from actiread::acti_read_gt3x()

use_extrapolation

If TRUE the function will apply extrapolation algorithm to the input signal, otherwise it will skip extrapolation but only linearly interpolate the signal to 100Hz.

use_filtering

If TRUE the function will apply bandpass filtering to the input signal, otherwise it will skip the filtering.

verbose

print diagnostic messages

dynamic_range

the dynamic ranges of the input signal. Passed to actimetrics::mims_default_extrapolation(). Only needed if use_extrapolation = TRUE

round_after_processing

Should the result be rounded to 3 decimal values after processing, to make similar to standard accelerometry?

Value

A processed data set

Perform step count calculation in a separate Python environment

Description

Perform step count calculation in a separate Python environment

Usage

py_acti_calculate_forest(
  ...,
  pyenv_function = function() {
     reticulate::import("forest")
 },
  show = FALSE
)

Arguments

...

arguments passed to acti_calculate_forest()

pyenv_function

function that loads the forest Python package. By default, it uses reticulate::py_import("forest") to import the package. If this function has an args argument, the output of pyenv_function will be re-assigned to args.

show

Logical, whether to show the standard output on the screen while the child process is running, passed to callr::r()

Value

The output from acti_calculate_forest().

Examples


  Sys.setenv("SSQ_PARALLEL" = 0)
  data = actiread::acti_read_gt3x(actiread::acti_example_gt3x())
  steps = py_acti_calculate_forest(data, sample_rate = 100)

Perform step count calculation in a separate Python environment

Description

Perform step count calculation in a separate Python environment

Usage

py_acti_calculate_stepcount(
  ...,
  pyenv_function = function() {
     stepcount::py_require_stepcount()
 },
  show = FALSE
)

Arguments

...

arguments passed to acti_calculate_stepcount()

pyenv_function

function that loads the stepcount Python package. By default, it uses reticulate::py_import("stepcount") to import the package. If this function has an args argument, the output of pyenv_function will be re-assigned to args.

show

Logical, whether to show the standard output on the screen while the child process is running, passed to callr::r()

Value

The output from acti_calculate_stepcount(). A tibble with minute-level time, steps, and walking columns.

Examples


  if (stepcount::have_stepcount()) {
    data = actiread::acti_read_gt3x(actiread::acti_example_gt3x())
    steps = py_acti_calculate_stepcount(data, sample_rate = 100)
  }