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2017
Journal Article
Titel
A privacy-aware fall detection system for hospitals and nursing facilities
Abstract
Hospitals and nursing facilities are confronted with a critical shortage of qualified nursing staff. At the same time, patient safety must not fall by the wayside. Therefore, we are facing a growing demand for assistance technologies that free up time for the medical responsibilities. We introduce a prototype of a fall detection system based on cameras and computer vision algorithms, which satisfies the high privacy demands of hospitals and nursing facilities. Our system explains its operations to patients and staff in order to establish transparency. Whenever we show video data to a nurse, it is either anonymized using image processing techniques or protected against misuse through usage control enforcement.