Every year, out-of-hospital cardiac arrest (OHCA) strikes 275,000 people in Europe, including 50,000 in Italy, where only 9% survive. Half of those who do are left with severe brain damage, largely due to delayed or inadequate CPR and defibrillation. Many cases occur in isolation, further slowing recognition and emergency response. Current CPR guidelines apply a one-size-fits-all approach, which fails to consider individual differences, often leading to suboptimal care.

To tackle this, researchers are developing cutting-edge technology, including artificial intelligence, smartphone applications, and advanced medical devices. An AI algorithm will analyze biosignals from wearable devices to predict cardiac events in advance, allowing at-risk individuals to seek medical attention before a crisis occurs. Surveillance camera footage will also be used to detect OHCA cases happening in isolation. Meanwhile, a smartphone app will mobilize nearby citizens as first responders, guiding them with augmented reality and internet-of-things technology to perform CPR and locate defibrillators quickly. Researchers will also refine CPR techniques by studying chest imaging data to determine the most effective compression methods and defibrillator pad placements for each patient.

By combining experimental studies, simulations, and interdisciplinary collaboration, this project aims to improve how OHCA is recognized and treated. With faster response times and more personalized interventions, these innovations could significantly reduce the global burden of cardiac arrest, saving lives and preventing long-term disability.