Reference research group: Biomedical Signal Interpretation & Computational Simulation (BSICoS)

The Biomedical Signal Interpretation and Computational Simulation Group (BSICoS) aims to develop biomedical signal processing and interpretation methods guided by physiology for making personalized clinical decisions (diagnosis, prognosis and therapy) in various pathological conditions of the cardiovascular, respiratory and autonomic nervous systems.

Therefore, the application of ICTs for the improvement of health is aimed, as well as the deepening of the knowledge of the physiology of biological systems observable through biomedical signals. Collaboration with clinical research teams and groups is essential for this, thus combining the backgrounds in the two fields, orienting the research to solve relevant clinical problems and facilitating the translation of the results to healthcare practice.

This general objective is specified in the 6 lines of work of the group:

1) Modeling and simulation of cardiac electrophysiology.

2) Non-invasive ECG-based markers for characterization of pathologies and identification of arrhythmic risk.

3) Intracardiac electrogram (EGM) signal processing to improve planning of cardiac interventions and therapy.

4) Non-invasive evaluation and quantification of the activity of the autonomic nervous system (ANS).

5) Processing and characterization of biomedical signals in respiratory pathologies.

6) Experimental characterization and in-vitro modeling of cardiac aging.

7) Long-term monitoring using wearable devices

The research is oriented towards some of the health problems that have the highest incidence in developed populations, such as the Aragonese (among them, coronary disease, atrial fibrillation, heart failure, stress, depression, asthma, apneas or the effect of aging itself) .