It is widely recognized how physiological signals have nonlinear and non-stationary behaviour due to their complex functionalities and the several functional, anatomical, electro-chemical interactions that continuously exist among different systems and organs (e.g., brain-heart interplay, cardio-respiratory coupling, sympatho-vagal balance). Consequently, physiological signals have been recently successfully modelled by exploiting nonlinear and complex methodologies. Notwithstanding, we believe that features beyond linearity are still largely unexplored both for the few robust quantifiers available, and for their functional physiological correlates. In this direction, we are focused on the definition, computation and modelling of novel efficient nonlinear quantifiers, and on their exploitation in physio-pathological experimental scenario in which such quantifier might be tested and validated.

Furthermore, in the broad context of dynamical series, and more specifically the physiological ones, the scientific community is well aware of the inevitable presence of an unwanted guest: ‘the dynamic noise’. Hundreds of techniques have been developed to perform signals’ pre-processing to discard artifact associated to environmental noise, motion, and other causes, but always persist the presence of what is defined as ‘physiological noise’. Our research question in this context is to describe such noise mathematically and statistically, and to exploit it as a marker of physiological and pathological state.


P. Castiglioni, L. Faes, G. Valenza, "Assessing Complexity in Physiological Systems through Biomedical Signals Analysis". Entropy, vol. 22, num. 1005, pp. 1-4, 2020.

A Ghouse, M Nardelli, G Valenza, "fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetics Tasks". Entropy, vol. 22, num. 7, pp. 1-17, 2020.

M Nardelli, EP Scilingo, G. Valenza, "Multichannel Complexity Index (MCI) for a Multi-Organ Physiological Complexity Assessment". Physica A: Statistical Mechanics and its Applications, vol. 530, 121543, pp. 1-13 2019.

A Greco, S Messerotti Benvenuti, C Gentili, D Palomba, EP Scilingo, and G Valenza, "Assessment of Linear and Nonlinear/Complex Heartbeat Dynamics in Subclinical Depression (Dysphoria)". Physiological Measurement, vol. 39, 034004, pp. 1-12, 2018.

R. Barbieri, EP Scilingo, and G. Valenza (Eds), "Complexity and Nonlinearity in Cardiovascular Signals, Series in Bioengineering". Springer International Publishing AG, Springer Nature, 2017.

Valenza, Gaetano, et al. "Complexity variability assessment of nonlinear time-varying cardiovascular control". Scientific reports 7.1 (2017): 1-15.