Package {asleep}

Title: Estimate Sleep from 'Accelerometry' Data
Version: 0.1.0
Description: Interfaces the 'asleep' python module https://github.com/OxWearables/asleep from Yuan (2024) <doi:10.1038/s41746-024-01148-y> to estimate sleep from 'accelerometry' data.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: assertthat, curl, lubridate, magrittr, readr, reticulate (≥ 1.42.0)
Suggests: tidyr, dplyr, ggplot2, testthat (≥ 3.0.0)
Config/testthat/edition: 3
URL: https://github.com/jhuwit/asleep, https://jhuwit.github.io/asleep/
BugReports: https://github.com/jhuwit/asleep/issues
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-07-24 20:53:38 UTC; johnmuschelli
Author: John Muschelli ORCID iD [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-04 13:50:08 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

lhs

A value or the magrittr placeholder.

rhs

A function call using the magrittr semantics.

Value

The result of calling rhs(lhs).

Run asleep Model on Data

Description

Run asleep Model on Data

Usage

asleep(
  file,
  outdir = NULL,
  min_wear_hours = 22L,
  time_shift = "0",
  report_light_and_temp = FALSE,
  pytorch_device = c("cpu", "cuda:0"),
  sample_rate = NULL,
  verbose = TRUE,
  force_download = FALSE
)

Arguments

file

accelerometry file to process, including CSV, CWA, GT3X, and GENEActiv bin files

outdir

output directory for CSVs and outputs

min_wear_hours

Min wear time in hours to be eligible for summary statistics computation. The sleepnet paper uses 22

time_shift

The number hours to shift forward or backward from the current device time. e.g. +1 or -1

report_light_and_temp

If true, it adds mean temp, and light columns to the predictions

pytorch_device

device to use for prediction for PyTorch.

sample_rate

Sample rate for the data, currently not used.

verbose

print diagnostic messages

force_download

force a download of the model, passed to sl_download_models()

Value

A list of outputs, including summaries, paths, and dataframes.

Examples


  file = system.file("extdata/example_sleep.csv.gz", package = "asleep")
  stopifnot(file.exists(file))
  if (asleep_check()) {
    sl_download_models()
    out = try({asleep(file = file, verbose = 2L)})
    if (inherits(out, "try-error")) {
      message(out)
      reticulate::py_last_error()
    } else {
      pred = out$predictions
    }
  }


  file = system.file("extdata/example_sleep.csv.gz", package = "asleep")
  df = readr::read_csv(file)
  if (asleep_check()) {
    out = asleep(file = df)
    st = out$predictions
  if (requireNamespace("ggplot2", quietly = TRUE) &&
      requireNamespace("tidyr", quietly = TRUE) &&
      requireNamespace("dplyr", quietly = TRUE)) {
    d = st[1:250,] %>%
      dplyr::mutate(
        time = lubridate::as_datetime(time),
        time_end = dplyr::lead(time)
      ) %>%
      dplyr::filter(!is.na(time_end))
    raw = df %>% dplyr::filter(time >= min(d$time) & time <= max(d$time))
    dat = raw %>%
      tidyr::gather(axis, value, -time)
    d = d %>% dplyr::mutate(activity_y = as.numeric(sleep_wake == "sleep"))
    dat %>%
       ggplot2::ggplot(ggplot2::aes(x = time, y = value, colour = axis)) +
       ggplot2::geom_step() +
       ggplot2::geom_segment(
         data = d,
         ggplot2::aes(
           x = time, xend = time_end,
           y = activity_y, yend = activity_y,
           linetype = sleep_wake
         ),
         colour = "black", linewidth = 1, inherit.aes = FALSE
       ) +
       ggplot2::labs(linetype = "Sleep/wake")
  }
 }

Get SSL Net -

Description

Get SSL Net -

Usage

get_sslnet()

sl_get_sslnet()

Value

A keras model representing the SSL Net.

Check the asleep Python Module

Description

Check the asleep Python Module

Usage

have_asleep()

asleep_check(...)

asleep_version(...)

Arguments

...

additional arguments to pass to reticulate::py_list_packages

Value

A logical value indicating whether the asleep Python module is available.

Examples


  if (have_asleep()) {
     asleep_version()
  }

Download asleep models to Cache

Description

Download asleep models to Cache

Usage

sl_download_models(force_download = FALSE)

Arguments

force_download

force a download of the model, even if it already exists at model_path

Value

A model from Python. sl_download_model returns a model file path.

Load asleep Model for Sleep Window Detector

Description

Load asleep Model for Sleep Window Detector

Usage

sl_load_model(model_path = NULL, force_download = FALSE, as_python = TRUE)

sl_download_model(model_path, ...)

Arguments

model_path

the file path to the model. If on disk, this can be re-used and not re-downloaded. If NULL, will download to the temporary directory

force_download

force a download of the model, even if it already exists at model_path

as_python

Keep model object as a python object

...

for sl_download_model, additional arguments to pass to curl::curl_download()

Value

A model from Python. sl_download_model returns a model file path.

Read a Data Set for asleep

Description

Read a Data Set for asleep

Usage

sl_read(file, resample_hz = "uniform", keep_pandas = FALSE)

Arguments

file

path to the file for reading

resample_hz

Target frequency (Hz) to resample the signal. If "uniform", use the implied frequency (use this option to fix any device sampling errors). Pass NULL to disable. Defaults to "uniform".

keep_pandas

do not convert the data to a data.frame and keep as a pandas data.frame

Value

A list of the data and information about the data

Note

The data P30_wrist100 is from https://ora.ox.ac.uk/objects/uuid:19d3cb34-e2b3-4177-91b6-1bad0e0163e7, where we took the first 180,000 rows, the first 30 minutes of data from that participant as an example.

Examples


  file = system.file("extdata/example_sleep.csv.gz", package = "asleep")
  if (asleep_check()) {
    out = sl_read(file, resample_hz = FALSE)
  }

Rename data for asleep

Description

Rename data for asleep

Usage

sl_rename_data(data)

sl_write_csv(data, path = tempfile(fileext = ".csv"))

Arguments

data

a data.frame of raw accelerometry

path

path to the CSV output file

Value

A data.frame of renamed columns