What is it about?

We developed an open source python software for the analysis of actigraphy recordings made with various devices. The functionalities range from data cleaning, calculations of rest-activity rhythm variables up to more advanced data processing techniques such as functional linear modelling, detrended fluctuation analysis or singular spectrum analysis.

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Why is it important?

We argue that there is a lack of open source software for the analysis of actigraphy recordings in the python ecosystem. The use of closed source commercial softwares not only limits the list of variables accessible by the researchers, it also hampers the current community efforts to make our research results more reliable and reproducible.


Actigraphy is a low-cost and unique ecological way to assess, in-situ, rest-activity, and more generally rhythmic, patterns on a large scale. Over the past decade, efforts have been made to provide researchers with access to large population-based datasets that open new epidemiological research avenues. However, the efforts should be matched with the development of adequate research softwares, like pyActigraphy, in order to fully benefit from these new datasets.

Grégory Hammad
University of Liège

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This page is a summary of: pyActigraphy: Open-source python package for actigraphy data visualization and analysis, PLoS Computational Biology, October 2021, PLOS, DOI: 10.1371/journal.pcbi.1009514.
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