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Python-based open source package for actigraphy data analysis

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pyActigraphy

Open-source python package for actigraphy 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 and MotionWatch 8
    • Condor Instrument: ActTrust 2
    • Daqtix: Daqtometer
    • Respironics: Actiwatch 2 and Actiwatch Spectrum (plus)
    • Tempatilumi (CE Brasil)

..

  • 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)

..

  • 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...

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.

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.