ParaDigMa: a Python toolbox for extracting Parkinson’s disease digital biomarkers from daily life wrist sensor data
Post et al., (2026). ParaDigMa: a Python toolbox for extracting Parkinson's disease digital biomarkers from daily life wrist sensor data. Journal of Open Source Software, 11(119), 9502, https://doi.org/10.21105/joss.09502
Authors
- Max A. Little (ORCID: https://orcid.org/0000-0002-1507-3822)
- Twan van Laarhoven (ORCID: https://orcid.org/0000-0001-7597-0579)
- Erik Post (ORCID: https://orcid.org/0000-0002-1937-9976)
- Luc J. W. Evers (ORCID: https://orcid.org/0000-0002-8241-5087)
- Vedran Kasalica (ORCID: https://orcid.org/0000-0002-0097-1056)
- Diogo C. Soriano (ORCID: https://orcid.org/0000-0002-9804-7477)
- Yordan P. Raykov (ORCID: https://orcid.org/0000-0003-0753-717X)
- Peter Kok
- Kars I. Veldkamp
- Nienke A Timmermans
- Hayriye Cagnan
- Bastiaan R. Bloem
Institutions
- University of Nottingham (GB)
- Radboud University Nijmegen (NL)
- Radboud University Medical Center (NL)
- Netherlands eScience Center (NL)
- Imperial College London (GB)
- Universidade Federal do ABC (BR)
- University of Birmingham (GB)
Publication Details
- Journal
- The Journal of Open Source Software
- Published
- 2026-03-26
- DOI
- https://doi.org/10.21105/joss.09502
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00