Smart IoT-based CPR training platform chest compression optimization and remote performance monitoring

Patricia Nataly Flores Ponce, Eynar Calle Viles, Edgar Roberto Ramos Silvestre and Rommer Alex Ortega-Martinez

SAP Biomedical & Chemical Engineering Innovation, 2026

Abstract: This paper presents the development of a smart Cardiopulmonary Resuscitation (CPR) training kit based on Internet of Things (IoT) principles. The system, designed to optimize chest compression techniques, integrates force and distance sensors, local processing through an ESP32 microcontroller, and MQTT wireless communication for remote monitoring and data analysis. Experimental validation with 20 novice participants showed improvements of 35 % in compression depth and 28 % in frequency within the recommended range (100–120 CPM) compared to standard commercial mannequins. Results showed an average feedback latency of 150ms and 94 % accuracy in depth measurement, establishing the feasibility of this IoT solution to improve CPR training quality, especially in resource-limited environments

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cwf:evkart:evk2026400

DOI: 10.56294/evk2026400

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