The SVisenS project aims to develop a real-time video analysis system for healthcare applications, addressing patient privacy, data security, and safety concerns by extracting medically relevant quantifiable features while discarding raw video data. Sensorizing cameras by transforming them into smart sensors, the system enables efficient clinical decision-making, patient monitoring, and emergency response. The extracted features minimize storage requirements, reduce costs, and preserve patient privacy. The approach targets four use cases: pediatric respiratory infections, stroke and transient ischemic attack, Parkinson's disease, and psychiatric conditions related to depression and schizophrenia. This research has the potential to advance healthcare data security and privacy, transforming data collection and improving patient care.

2026

2029