Exploiting CCTV Cameras for Hand Hygiene Recognition in ICU

The monitoring of hand hygiene activities can effectively reduce the infection and contamination in the Intensive Care Unit (ICU). In this paper, we created a clinical dataset using CCTV cameras installed in ICU to explore the feasibility of recognizing hand washing steps of clinicians. A video processing architecture including hand landmark detection and classification is presented. Such a system can potentially be used to alarm the clinicians to follow the guidelines of hand hygiene. The experimental results show that the average accuracy of our methodology can achieve 95\% under personalized model, 56\% under generalized model. The preliminary results suggest that hand hygiene is subject-dependent, which is related to the palm size and washing habit of individuals. The cross-subject modeling or subject-adaptive learning can be applied to further improve the accuracy of recognition towards a more generalized solution. The insights of study are helpful for designing an hand hygiene scoring and alarming system as a part of hospital IoT.