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PDkit is a python module that provides a comprehensive toolkit for the management and processing of Parkinson’s symptoms performance data captured by high-use-frequency smartphone apps and continuously by wearables. PDkit facilitates the application of an extensive collection of methods and techniques across all stages of the Parkinson’s information processing pipeline. Although inherently flexible, PDkit currently prioritises functionalities critical to therapeutic clinical trial delivery rather than general patient care.

More information is available in the following paper:

Stamate C, Saez Pons J, Weston D, Roussos G (2021) PDKit: A data science toolkit for the digital assessment of Parkinson’s Disease. PLoS Comput Biol 17(3): e1008833. doi:10.1371/journal.pcbi.1008833 https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008833

An example of how PDkit is used in clinical strudies of Parkinson’s can be found in:

Jha, A., Menozzi, E., Oyekan, R. et al. The CloudUPDRS smartphone software in Parkinson’s study: cross-validation against blinded human raters. npj Parkinsons Dis. 6, 36 (2020). https://doi.org/10.1038/s41531-020-00135-w

The PDkit currently supports directly the following apps: cloudUPDRS, mPower, HopkinsPD and OPDC.

Full documentation of PDkit features is available on readthedocs.

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Release files for pdkit 1.4.4

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