Deep Learning-Based Computer Vision for Real-Time Intravenous Drip Infusion Monitoring

This paper explores the use of deep learning-based computer vision for real-time monitoring flow in intravenous (IV) infusions. IV infusions are among most common therapies hospitalized patients and, given that both over-infusion and under-infusion can cause severe damages, rate fluid being administered to is very important their safety. The proposed system uses a camera film drip infusion kit algorithm classify acquired frames into two different states: with drop has just begun take shape well-formed drop. alternation these states used count drops derive measurement drip. usage as sensing element makes safe medical environments easier be integrated current health facilities. Experimental results reported confirm accuracy its capability produce estimates. method therefore effectively adopted implement control systems.