pyActigraphy: Open-source python package for actigraphy data visualization and analysis

Over the past 40 years, actigraphy has been used to study rest-activity patterns in circadian rhythm and sleep research. Furthermore, considering its simplicity of use, there is a growing interest in the analysis of large population-based samples, using actigraphy. Here, we introduce pyActigraphy ,...

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Vydáno v:PLoS computational biology Ročník 17; číslo 10; s. e1009514
Hlavní autoři: Hammad, Grégory, Reyt, Mathilde, Beliy, Nikita, Baillet, Marion, Deantoni, Michele, Lesoinne, Alexia, Muto, Vincenzo, Schmidt, Christina
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Public Library of Science 19.10.2021
Public Library of Science (PLoS)
Témata:
Actigraphy - methods
Activity patterns
Algorithms
Alzheimer's disease
Biology and Life Sciences
Brain research
Circadian rhythm
Circadian rhythms
Computational Biology - methods
Computer and Information Sciences
Data analysis
Data Visualization
Datasets
Diaries
Engineering and Technology
Humans
Methods
Neurosciences & behavior
Neurosciences & comportement
Open source software
Patient monitoring
Physical Sciences
Python (Programming language)
Research and Analysis Methods
Science Policy
Sciences sociales & comportementales, psychologie
Scientific visualization
Signal processing
Signal Processing, Computer-Assisted
Sleep
Sleep - physiology
Social & behavioral sciences, psychology
Software
Visualization
Belgium
ISSN:1553-7358, 1553-734X, 1553-7358
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Popis
Shrnutí:Over the past 40 years, actigraphy has been used to study rest-activity patterns in circadian rhythm and sleep research. Furthermore, considering its simplicity of use, there is a growing interest in the analysis of large population-based samples, using actigraphy. Here, we introduce pyActigraphy , a comprehensive toolbox for data visualization and analysis including multiple sleep detection algorithms and rest-activity rhythm variables. This open-source python package implements methods to read multiple data formats, quantify various properties of rest-activity rhythms, visualize sleep agendas, automatically detect rest periods and perform more advanced signal processing analyses. The development of this package aims to pave the way towards the establishment of a comprehensive open-source software suite, supported by a community of both developers and researchers, that would provide all the necessary tools for in-depth and large scale actigraphy data analyses.
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COGNAP
info:eu-repo/grantAgreement/EC/H2020/757763
scopus-id:2-s2.0-85117522932
The authors have declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1009514