Intelligent CPR training system with remote monitoring: Applicability in improving survival in cardiorespiratory arrests

Patricia Nataly Flores Ponce
Universidad Privada del Valle - Univalle


Abstract

This paper addresses Out-of-hospital cardiopulmonary arrest (OCARA) as one of the leading causes of death globally. Recent studies, such as the American Heart Association (AHA) registries, confirm that less than 10% of victims survive to hospital discharge when immediate CPR is not applied. This figure contrasts with survival rates of 15–30% in settings where high-quality CPR is implemented by bystanders or first responders, highlighting the critical importance of early intervention. An IoT CPR training system is presented that combines precision sensors, wireless communication (MQTT), and a web-based platform to optimize training for non-expert users. The system assesses critical parameters such as depth (5–6 cm), rate (100–120 compressions/min), and strength of chest compressions, providing immediate visual and auditory feedback. A 40% improvement in adherence to American Heart Association (AHA) standards was observed. The results highlight the system's potential to reduce CPA mortality in various situations and settings with limited access to medical training, especially in outpatient settings.