In this webinar, Dr. Luc Evers and PhD candidate Erik Post present an opensource toolbox for wearable data they have developed at the Center for Expertise for Parkinson and Movement Disorders, Radboud University Medical Center (Nijmegen, NL). Wearable sensors offer exciting opportunities to study Parkinson’s disease in daily life, but turning real-life, high-frequency sensor data into reliable and meaningful measures can be challenging. To help researchers tackle this challenge, Dr. Evers and Erik developed ParaDigMa - an open-source, device-agnostic Python toolbox with validated pipelines to quantify tremor, arm swing during gait and autonomic changes from continuous, wrist sensor data. In this webinar, they demonstrate its key functionalities, and walk you through how you can use it with your own sensor data. This webinar was organized by the the Michael J. Fox Foundation's Data Community of Practice (DCoP). Do you have ideas or suggestions for other webinar topics you would like to see? Is there a tool you feel the community would benefit from highlighting? Let us know by leaving your thoughts in this thread: Seeking Webinar Ideas and Requests from the Community, or by contacting researchcommunity@michaeljfox.org. For those interested in joining or contributing to the DCoP, please visit rcop.michaeljfox.org.