Heart rate variability (HRV), generally defined as the variations of heart rate (HR) around its mean, is an important quantitative marker of cardiovascular regulation by the autonomic nervous system. From the first HRV electrocardiographic studies, over 40 years ago, it was clear that R-wave to R-wave (R-R) interval dynamics contain well-defined rhythms associated with autonomic tone, encouraging further investigation and leading, in 1996, to definition of a set of standard HRV measures. To date, despite HRV has been evaluated in thousands of studies to characterize and diagnose diseases that affect the autonomic nervous system, accurate personalized solutions for clinical and everyday monitoring are still under scrutiny. With the advent of wearable technology able to accurately detect the heartbeat, HRV analysis provides promising new avenues for monitoring, diagnosis and prevention of cardiovascular health. This presentation focuses on our recently derived definitions of HR and HRV based on explicit point process Bayesian probability models. Point process models give a physiologically sound representation of the stochastic structure generating the heartbeat and they allow for instantaneous assessment of fast, non-stationary dynamics. Our current work is focusing on incorporating the point process framework into nonlinear models of cardiovascular control and autonomic regulation, with inclusion of other cardiovascular variables such as arterial blood pressure and respiration, as well as combining HRV estimates with fMRI brain imaging in order to identify human brain correlates of autonomic modulation. The presented dynamic statistical measures yield important implications for research studies of cardiovascular and autonomic regulation, and they provide the basis for potential real-time indicators for ambulatory, wearable monitoring and instantaneous assessment of autonomic control in clinical settings.

The NECSTLab is a DEIB laboratory, with different research lines on advanced topics in computing systems: from architectural characteristics, to hardware-software codesign methodologies, to security and dependability issues of complex system architectures.