David Verweij

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IDEA-FAST is a 5.5 year Horizon 2020 EU project that aims to determine 'digital endpoints' to assess fatigue, sleep, and activities of daily living in neurodegenerative and immune-mediated diseases - such as Parkinson’s disease and Rheumatoid Arthritis. Through an extensive selection protocol and real-world testing, a set of sensing devices is being used by patients in a large-scale clinical trial. My software engineering role, within 'work package 3', includes the streamlining of data collection of the various sensing technologies (each with their own APIs and data structures). I thereby provide technical support for the clinicians 'on-the-ground' - partially through feeding back the quality and progress of data collection. This includes the development of a patient-facing mobile app to do so consistently - and independently - across the technologies used.


To streamline the data collection, we set up a server architecture based on Python which we monitor using Apache Airflow. It interfaces with both SQL and No-SQL databases, and hosts a variety of services - including surveys (LimeSurvey), inventory management (Snipe-it), documentation (Jekyll), and support ticketing (Zammad). The patient facing app is a React-Native app that interfaces with the same server.


  • Server (Digital Ocean, Docker, Traefik, SQL),
  • Middleware (Python, Celery, MongoDB, FastApi, Apache Airflow),
  • Technical support (LimeSurvey, Snipe-it, Jekyll, Zammad),
  • Mobile App (React Native)


Project Website, Code repository