SciKit Digital Health (SKDH) is a compilation of algorithm implementations based on previous work. The goal of SKDH is to provide commonly used algorithms in mobility research from wearable inertial sensors under a common framework, with sensible defaults, and an easily extensible framework that allows for customization based on the end-users needs. To this end, SKDH provides modules for data ingestion, pre-processing, and processing in gait, sit-to-stand, activity, and sleep, making going from raw data to digital health biomarkers fast and easy. Join authors Yiorgos Christakis, MSc and Lukas Adamowicz, MSc, I Quantitative Scientists at Pfizer, as they present their publication, ” SciKit Digital Health: Python Package for Streamlined Wearable Inertial Sensor Data Processing at DiMe’s October Journal Club. Register now for this #AskMeAnything and join the discussion on sensor data processing!