In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 17, No. 10 ( 2021-10-19), p. e1009514-
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1009514
DOI:
10.1371/journal.pcbi.1009514.g001
DOI:
10.1371/journal.pcbi.1009514.g002
DOI:
10.1371/journal.pcbi.1009514.g003
DOI:
10.1371/journal.pcbi.1009514.g004
DOI:
10.1371/journal.pcbi.1009514.t001
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2021
detail.hit.zdb_id:
2193340-6
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