SWEATHEART: Applied Mathematics to Personalise and Optimise Sports Performance

Elisabetta de Giovanni and Tomás Teijeiro, with the collaboration of Iñigo Urteaga within the SWEATHEART project, are developing an innovative intelligent monitoring system designed to transform raw data from standard commercial sensors into actionable insights for athletes and coaches alike. The breakthrough methodology and its practical applications were recently highlighted in the science and technology TV programme Teknopolis.

Modern athletes routinely train with commercial smartwatches and wearable devices that monitor heart rate, blood flow, respiration, and galvanic skin response. However, a significant portion of this high-resolution physiological data remains underutilised, often reduced to basic averages. The objective of this project is to unlock that hidden potential by creating advanced mathematical models that translate standard sensor signals into highly precise, quantifiable performance metrics.

By capturing and analysing the heart's electrical signals (ECG), blood flow fluctuations, breathing patterns, and the skin's response to sweat, these models provide a comprehensive, real-time overview of an athlete's physiological state. This enables coaches to make data-driven decisions, tailors training workloads to individual capacities, and prevents overtraining or fatigue-induced injuries.

This research effectively bridges the gap between raw biometric signals and elite athletic preparation, ensuring that standard consumer technology can deliver laboratory-grade insights. See the full interview here:
 

This project has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Sklodowska-Curie actions (Grant Agreement 101202439 - SWEATHEART).