Article (Scientific journals)
pyActigraphy: Open-source python package for actigraphy data visualization and analysis
Hammad, Grégory; Reyt, Mathilde; Beliy, Nikita et al.
2021In PLoS Computational Biology, 17 (10), p. 1009514
Peer Reviewed verified by ORBi
 

Files


Full Text
Hammad_2021_PlosComputBiol.pdf
Publisher postprint (1.9 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Abstract :
[en] The possibility to continuously record locomotor movements using accelerometers (actigraphy) has allowed field studies of sleep and rest-activity patterns. It has also enabled large-scale data collections, opening new avenues for research. However, each brand of actigraph devices encodes recordings in its own format and closed-source proprietary softwares are typically used to read and analyse actigraphy data. In order to provide an alternative to these softwares, we developed a comprehensive open-source toolbox for actigraphy data analysis, pyActigraphy. It allows researchers to read actigraphy data from 7 different file formats and gives access to a variety of rest-activity rhythm variables, automatic sleep detection algorithms and more advanced signal processing techniques. Besides, in order to empower researchers and clinicians with respect to their analyses, we created a series of interactive tutorials that illustrate how to implement the key steps of typical actigraphy data analyses. As an open-source project, all kind of user’s contributions to our toolbox are welcome. As increasing evidence points to the predicting value of rest-activity patterns derived from actigraphy for brain integrity, we believe that the development of the pyActigraphy package will not only benefit the sleep and chronobiology research, but also the neuroscientific community at large.
Research center :
GIGA CRC (Cyclotron Research Center) In vivo Imaging-Aging & Memory - ULiège
Disciplines :
Neurosciences & behavior
Neurosciences & behavior
Neurosciences & behavior
Author, co-author :
Hammad, Grégory  ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging - Sleep and chronobiology
Reyt, Mathilde ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging - Sleep and chronobiology
Beliy, Nikita ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging - Aging & Memory
Baillet, Marion ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging
Deantoni, Michele ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging - Sleep and chronobiology
Lesoinne, Alexia ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging - Sleep and chronobiology
Muto, Vincenzo  ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging
Schmidt, Christina  ;  Université de Liège - ULiège > GIGA CRC In vivo Imaging - Sleep and chronobiology
Language :
English
Title :
pyActigraphy: Open-source python package for actigraphy data visualization and analysis
Publication date :
19 October 2021
Journal title :
PLoS Computational Biology
ISSN :
1553-734X
eISSN :
1553-7358
Publisher :
Public Library of Science, United States - California
Volume :
17
Issue :
10
Pages :
e1009514
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
H2020 - 757763 - COGNAP - To nap or not to nap? Why napping habits interfere with cognitive fitness in ageing
Name of the research project :
COGNAP
Funders :
CER - Conseil Européen de la Recherche [BE]
CE - Commission Européenne [BE]
Available on ORBi :
since 26 January 2022

Statistics


Number of views
163 (6 by ULiège)
Number of downloads
136 (3 by ULiège)

Scopus citations®
 
12
Scopus citations®
without self-citations
11
OpenCitations
 
8

Bibliography


Similar publications



Contact ORBi