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

Grégory HammadMathilde ReytNikita BeliyMarion BailletMichele DeantoniAlexia LesoinneVincenzo MutoChristina Schmidt
Published in: PLoS computational biology (2021)
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.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • data analysis
  • atrial fibrillation
  • sleep quality
  • heart rate
  • blood pressure