Smart iot-based cpr training platform chest compression optimization and remote performance monitoring

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dc.contributor.authorPatricia Nataly Flores Ponce
dc.contributor.authorEynar Calle Viles
dc.contributor.authorEdgar Roberto Ramos Silvestre
dc.contributor.authorRommer Alex Ortega-Martinez
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T19:54:07Z
dc.date.available2026-03-22T19:54:07Z
dc.date.issued2025
dc.description.abstractThis 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
dc.identifier.doi10.56294/evk2026400
dc.identifier.urihttps://doi.org/10.56294/evk2026400
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/78801
dc.relation.ispartofeVitroKhem
dc.sourceUniversidad Privada del Valle
dc.subjectComputer science
dc.subjectCardiopulmonary resuscitation
dc.subjectWireless
dc.subjectTraining (meteorology)
dc.subjectCompression (physics)
dc.subjectMQTT
dc.subjectInternet of Things
dc.subjectReal-time computing
dc.subjectData compression
dc.subjectLatency (audio)
dc.titleSmart iot-based cpr training platform chest compression optimization and remote performance monitoring
dc.typearticle

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