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Releases: Trybnetic/paat

v1.0.0b10

16 Jul 07:19
@Trybnetic Trybnetic
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Full Changelog: v1.0.0b9...v1.0.0b10

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Trybnetic
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v1.0.0

16 Jul 07:46
@Trybnetic Trybnetic
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The Physical Activity Analysis Toolbox (PAAT) is a versatile Python package designed to analyze physical activity
data. It is used in research and health-related fields to process raw acceleration data collected from the hip. It
supports importing, cleaning, and preprocessing raw data, and includes algorithms to classify time in bed and non wear
time. Furthermore, it supports estimating various physical activity levels such as moderate-to-vigorous physical
activity or sedentary behavior, with customizable thresholds from multiple metrics. These estimates can be aggregated
and used for further statistical analysis or be used directly for more sophisticated physical activity pattern analysis.
Additionally, PAAT is extensible, allowing users to add custom algorithms or modules, and it integrates well with
other data analysis tools within the Python ecosystem.

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v1.0.0b9

05 May 06:10
@Trybnetic Trybnetic
f2bf96b
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Full Changelog: v1.0.0b8...v1.0.0b9

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Trybnetic
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v1.0.0b8

05 Feb 10:57
@Trybnetic Trybnetic
3fd21c2
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Full Changelog: v1.0.0b7...v1.0.0b8

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Trybnetic
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v1.0.0b7

11 Nov 13:54
@Trybnetic Trybnetic
095935f
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New Contributors

Full Changelog: v1.0.0b6...v1.0.0b7

Contributors

freddie-freeloader, Trybnetic, and claaslendt
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paat v1.0.0b6

03 Oct 12:45
@Trybnetic Trybnetic

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The physical activity analysis toolbox (PAAT) is a comprehensive toolbox to analyze raw acceleration data. We developed all code mainly for analyzing ActiGraph data (GT3X files) in large sample study settings where manual annotation and analysis is not feasible. Most functions come along with scientific papers describing the methodology in detail. Even though, the package was and is primarily develop for analyzing ActiGraph data, we warmly welcome contributions for other clinical sensors as well!

This is the first more or less stable release which will be uploaded to zenodo. This is still a beta release which might be subject to changes, but it is uploaded to allow reproducible usage nonetheless.

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