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pyActigraphy

Open-source python package for actigraphy and light exposure data visualization and analysis.

This package is meant to provide a comprehensive set of tools to:

• read native actigraphy data files with various formats:

  • Actigraph: wGT3X-BT
  • CamNtech: Actiwatch 4, 7, L(-Plus) and MotionWatch 8
  • Condor Instrument: ActTrust 2
  • Daqtix: Daqtometer
  • Respironics: Actiwatch 2 and Actiwatch Spectrum (plus)
  • Tempatilumi (CE Brasil)

..

• NEW read actigraphy data format from the MESA dataset <https://sleepdata.org/datasets/mesa>, hosted by the National Sleep Research Resource <https://sleepdata.org>.

• NEW read actigraphy data files produced by the accelerometer <https://biobankaccanalysis.readthedocs.io/en/latest/index.html>_ package that can be used to calibrate and convert raw accelerometer data recorded with:

  • Axivity: AX3, device used by UK Biobank,
  • Activinsights: GENEActiv, used by the Whitehall II study.

..

• NEW read light exposure data recorded by the aforementioned devices (when available)

• clean the raw data and mask spurious periods of inactivity

• produce activity profile plots

• visualize sleep agendas and compute summary statistics

• calculate typical wake/sleep cycle-related variables:

  • Non-parametric rest-activity variables: IS(m), IV(m), RA
  • Activity or Rest fragmentation: kRA, kAR
  • Sleep regularity index (SRI)

..

• NEW compute light exposure metrics (TAT, :math:MLit^{500}, summary statistics, ...)

• automatically detect rest periods using various algorithms (Cole-Kripke, Sadeh, ..., Crespo, Roenneberg)

• perform complex analyses:

  • Cosinor analysis
  • Detrended Fluctuation Analysis (DFA)
  • Functional Linear Modelling (FLM)
  • Locomotor Inactivity During Sleep (LIDS)
  • Singular Spectrum Analysis (SSA)
  • and much more...

Citation

We are very pleased to announce that the v1.0 <https://github.com/ghammad/pyActigraphy/releases/tag/v1.0>_ version of the pyActigraphy package has been published. So, if you find this package useful in your research, please consider citing:

Hammad G, Reyt M, Beliy N, Baillet M, Deantoni M, Lesoinne A, et al. (2021) pyActigraphy: Open-source python package for actigraphy data visualization and analysis. PLoS Comput Biol 17(10): e1009514. https://doi.org/10.1371/journal.pcbi.1009514

pyLight

In the context of the Daylight Academy Project, The role of daylight for humans <https://daylight.academy/projects/state-of-light-in-humans>_ and thanks to the support of its members, Dr. Mirjam Münch and Prof. Manuel Spitschan <https://github.com/spitschan>, a pyActigraphy module for analysing light exposure data has been developed, pyLight. This module is part of the Human Light Exposure Database and is included in pyActigraphy version v1.1 <https://github.com/ghammad/pyActigraphy/releases/tag/v1.1> and higher.

A manuscript describing the pyLight module is available as a preprint <https://osf.io/msk9n/>_.

Code and documentation

The pyActigraphy package is open-source and its source code is accessible online <https://github.com/ghammad/pyActigraphy>_.

An online documentation of the package is also available here <https://ghammad.github.io/pyActigraphy/index.html>. It contains notebooks <https://ghammad.github.io/pyActigraphy/tutorials.html> illustrating various functionalities of the package. Specific tutorials for the processing and the analysis of light exposure data with pyLight are also available.

Installation

In a (bash) shell, simply type:

• For users:

.. code-block:: shell

pip3 install pyActigraphy

To update the package:

.. code-block:: shell

pip3 install -U pyActigraphy

• For developers:

.. code-block:: shell

git clone [email protected]:ghammad/pyActigraphy.git cd pyActigraphy/ git checkout develop pip3 install -e .

Quick start

The following example illustrates how to calculate the interdaily stability with the pyActigraphy package:

.. code-block:: python

import pyActigraphy rawAWD = pyActigraphy.io.read_raw_awd('/path/to/your/favourite/file.AWD') rawAWD.IS() 0.6900175913031027 rawAWD.IS(freq='30min', binarize=True, threshold=4) 0.6245582891144925 rawAWD.IS(freq='1H', binarize=False) 0.5257020914453097

Contributing

There are plenty of ways to contribute to this package, including (but not limiting to):

• report bugs (and, ideally, how to reproduce the bug)
• suggest improvements
• improve the documentation

Authors

• Grégory Hammad @ghammad <https://github.com/ghammad>_ - Initial and main developer
• Mathilde Reyt @ReytMathilde <https://github.com/ReytMathilde>_

See also the list of contributors <https://github.com/ghammad/pyActigraphy/contributors>_ who participated in this project.

License

This project is licensed under the GNU GPL-3.0 License - see the LICENSE <LICENSE>_ file for details

Acknowledgments

• Aubin Ardois @aardoi <https://github.com/aardoi>_ developed the first version of the MTN class during his internship at the CRC, in May-August 2018.
• The CRC colleagues for their support, ideas, etc.