BSICoS

Biomedical Signal Interpretation and Computational Simulation
foto_grupo BSICoS

The Biomedical Signal Interpretation and Computational Simulation (BSICoS) group focuses its activity on the processing, interpretation and Computer Simulation of biomedical signals.

The main objective of the group is the development of methods for biomedical signal processing, driven by the physiology, for personalized interpretation (diagnosis, prognosis and therapy) of the conditions of the cardiovascular, respiratory and autonomic nervous systems and their interactions.

The goal is to improve the impact of ICTs in health and further understanding the functioning of biological systems that can be observed through noninvasive signals. Key to this is working with clinical teams and research groups that combine the experiences of the two areas, direct research to solve relevant clinical problems and facilitate the transfer of results to clinical practice.

Projects

The objective of this Project is to model the psychophysiological response of subjects exposed to hyperbaric environments, identifying the physiological parameters that better characterize this response. This will allow, in the near future, an early identification of dysfunctional psychophysiological states that can be risky for the health of the subjects.

By developing biological ventricular assist devices (BioVADs), BRAV3 will bring a quantum leap in regenerative medicine and its translation towards the clinic, as well as impact the development of novel medical technologies whilst greatly advancing our knowledge on human heart development.
BRAVE

The project is expected to make major scientific contributions to depression monitoring, to the characterization and interpretation of ANS from the joint analysis of physiological signals, and to daily-life ANS monitoring.
MINECO

In this project, several of the main technological challenges in relation to these arrhythmias are addressed

This project aims at providing a comprehensive characterization of cardiac changes induced by the mentioned highly prevalent CVDs as well as by physiological aging and non-cardiac diseases/conditions associated with increased cardiovascular risk.

Completed projects (since 2020)