Service Description

Accelerometer Data Processing with GGIR is an online training designed to help researchers, analysts, and students master the use of the open-source R package GGIR for standardized and reproducible analysis of raw accelerometer data. Accelerometers are increasingly used in health, behavioral, and epidemiological research to objectively measure physical activity, sleep, and sedentary behavior. GGIR enables robust and transparent processing of raw data, supporting high-quality, reproducible research outcomes. This course offers a practical and accessible path to learning the full GGIR workflow—from raw data import and calibration to the generation of key metrics and quality control. Participants will explore the core functionalities of GGIR, develop reproducible pipelines, and understand how to interpret the outputs in a research context. Training structure: Participants receive 3 months of access to a dedicated Moodle-based learning platform, which includes: - Pre-recorded theoretical video sessions - Hands-on coding tutorials - Downloadable materials and exercises To complement the self-paced learning, the training includes three live collective tutorial sessions—one per month—each lasting 90 to 120 minutes. These sessions provide an opportunity to ask questions, receive guidance, and connect with the instructor and fellow participants. Key topics include: - An optional module on learning R essentials to use GGIR - Introduction to raw accelerometry and the role of GGIR - Preparing and organizing data for processing - Core GGIR functionalities and parameter settings - Batch processing, troubleshooting, and interpreting results - Best practices for reproducibility and standardization By the end of the training, participants will be equipped to confidently implement a GGIR-based pipeline tailored to their research needs, ensuring that their data processing is both efficient and scientifically rigorous. No prior experience with GGIR or R is required, though you are expected to have R and RStudio installed and ready to use. All necessary course materials, scripts, and sample datasets will be provided.