Protocol for anonymizing data collected in scientific research: biomedical signals, videos, and qualitative data

Research in healthcare has been transformed by the growing complexity and richness of the data collected. Despite this, data sharing practices remain limited, and research shows that only a small proportion of published medical articles make their data publicly available. This gap compromises the scientific principles of reproducibility and replicability, which are essential for validating results and accelerating discoveries. Data collection and sharing face significant challenges, such as high costs, logistical difficulties, and problems in anonymizing sensitive data, especially biomedical signals. Several techniques have been developed to address these challenges. In this scenario, this work proposes a comprehensive method for anonymizing multi-modal biomedical data, integrating physiological signals, structured clinical data, and audiovisual content, with the work itself being a use case for the proposed method.