Automated monitoring of IVD device analysis processes using machine learning and computer vision techniques

This study presents an automated monitoring system which analyze In Vitro Diagnostics (IVD) device processes in real-time. It captures images of elements involved in aspiration and dispensing of liquids, namely tips, during critical moments of the diagnostic session. The acquired images are processed using Machine Learning and Computer Vision algorithms, allowing continuous monitoring of the diagnostic process. The study focuses on the critical operation of gripping tips during the session.