SciKit Digital Health: Python Package for Streamlined Wearable Inertial Sensor Data Processing

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. Authors Yiorgos Christakis, MSc and Lukas Adamowicz, MSc, I Quantitative Scientists at Pfizer presented their publication, ” SciKit Digital Health: Python Package for Streamlined Wearable Inertial Sensor Data Processing at DiMe’s October Journal Club in an ask me anything format.

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