We investigate methods for assessing cardiovascular (CV) function through the analysis of pulse wave signals, including blood pressure, blood flow, and photoplethysmogram (PPG) waves. These signals can be measured in vivo using various devices (including wearable sensors). They are influenced by the heart, vasculature, respiratory system, and autonomic nervous system, making them a valuable source of information for evaluating human health.

We create innovative models to simulate pulse wave signals across various physiological and patho-physiological conditions. We develop methods to calibrate these models and understand the physical mechanisms underlying their results. Additionally, we explore signal processing techniques to assess the cardiovascular, respiratory, and autonomic nervous systems. We use these tools to study clinically relevant problems, typically combining in silico and in vivo data.

Our research publications are listed here.