Biosignals and
Information Theory
Laboratory
University of Palermo
Who we are
We are a team of biomedical and electronic engineers developing data science technologies to investigate the dynamics and structure of complex physiological systems.
Our research ranges from statistical physics to computational neuroscience and physiology and focuses on the use of signal processing, time series analysis and information theory to assess interactions in network systems, with application spanning from brain connectivity to cardiovascular oscillations and network physiology.
News and Updates - 2024
Projects: PRIN project "High-Order Dynamical Networks in Computational Neuroscience and Physiology: an Information-Theoretic Framework" - HONEST - project meeting in Palermo on June 10, 2024 - see flyer here
Conference NetSci 2024: we have presented the work: High-Order Interactions As Pairwise Networks: an Information Dynamics Approach
Last papers:Â
May 2024: Chiara's paper "Comparison of entropy rate measures for the evaluation of time series complexity: Simulations and application to heart rate and respiratory variability" has been published in Biocybernetics and Biomedical Engineering
Apr 2024: Gabriele's paper "Wearable Ring-Shaped Biomedical Device for Physiological Monitoring through Finger-Based Acquisition of Electrocardiographic, Photoplethysmographic, and Galvanic Skin Response Signals: Design and Preliminary Measurements" has been published in Biosensors journal
Mar 2024: Laura's paper 'A method to assess linear self-predictability of physiologic processes in the frequency domain: application to beat-to-beat variability of arterial compliance', is accepted in Frontiers in Network Physiology
Mar 2024: Gorana's paper 'Assessing high-order links in cardiovascular and respiratory networks via static and dynamic information measured', in press in IEEE Open Journal of Engineering in Medicine and Biology
Feb 2024: Yuri's paper 'Measuring Connectivity in Linear Multivariate Processes with Penalized Regression Techniques' is accepted in IEEE Access !
Jan 2024: Check out our preprint about measurement of hierarchically-organized interactions in networks