Brugada syndrome is a genetic disorder that disrupts heart rhythm. It predominantly affects young men and carries the risk of sudden cardiac death, thus representing a major social concern.

Traditionally, diagnosis of the syndrome has been based on the identification of specific visible patterns on the electrocardiogram (ECG), particularly with reference to ventricular abnormalities. Recent discoveries, however, have shifted the focus to the atria, revealing new diagnostic possibilities.

This shift is part of collaborative work between the Biomedical Signal Processing (BSP) research group of the Institute of Digital Technologies for Personalized Healthcare (MeDiTech), led by Francesca Faraci, and the Cardiocentro Ticino Institute of the Ente Ospedaliero Cantonale (EOC).

As part of this study, Beatrice Zanchi, a MeDiTech PhD student, developed an artificial intelligence system that identifies Brugada syndrome by focusing exclusively on atrial abnormalities. This approach focuses on the analysis of the P wave, a specific part of the ECG related to atrial activity.

This study challenged the conventional understanding of Brugada syndrome and opened new perspectives for innovative diagnostic methods, promoting early detection and intervention.

Significant findings were published in EP Europace Journal, a journal of Cardiology, Cardiovascular Medicine and Medical Physiology published by Oxford University Press:

Zanchi, B., Faraci, F. D., Gharaviri, A., Bergonti, M., Monga, T., Auricchio, A., & Conte, G. (2023). Identification of Brugada syndrome based on P-wave features: an artificial intelligence-based approach. Europace, 25(11), euad334.