Healthcare professionals rarely witness what actually happens in the very first moments of an out-of-hospital cardiac arrest. What we know is most often reconstructed from the narratives of bystanders or family members who were present at the scene. In this study, we analyzed 145 out-of-hospital cardiac arrests captured by surveillance cameras. These videos provide a unique opportunity to directly observe the earliest moments of collapse, revealing recurrent signs of cardiac arrest, frequently misinterpreted behaviors, and a critical delay between event recognition and the initiation of resuscitative efforts. The insights gained may help improve education, public awareness, and the development of strategies aimed at earlier recognition and more timely intervention. Building on these findings, we are working with the Politecnico di Milano to train an artificial intelligence algorithm capable of automatically detecting cardiac arrest from surveillance video footage, with particular potential impact in cases of unwitnessed cardiac arrest. This work is part of the EU-funded TIME-CARE project. Read the article on Resuscitation: sciencedirect.com/science/ar… #CardiacArrest #CardiopulmonaryResuscitation #Innovation #Research #TIMECARE #SanRaffaele