Computational biomedicine uses patient-specific image-based computational modeling to understand the mechanisms driving certain diseases. Modeling is an intrinsic component of most biomedical engineering research.
In this research pillar, we focus on blood flow and aneurysms, the biomechanics of eye movement, and the extraction of wellness indicators from video feature analyses.
Our areas of expertise include:
Aneurysm risk assessment through computational modeling and minimally invasive procedures
This research examines the blood flow in brain aneurysms to improve understanding of the causes, enhance aneurysm risk assessment, and evaluate devices and minimally invasive procedures. We develop techniques and tools for modeling blood flows from 3D medical images and apply these techniques to study cerebrovascular diseases and their treatment. Principal investigator: Juan Raul Cebral.
Data-driven biomechanical simulation
Our focus is applying biomechanical models and computational simulation complemented by experimental data to advance our knowledge of human movement and to improve treatment of movement disorders. Our computational modeling approach enhances understanding of the basic components involved in movement in a constructive way. In collaboration with clinicians, we study the biomechanics of strabismus and pelvic floor disorders in order to identify potential new treatment regimes. Principal investigator: Qi Wei.
Signal and video analytics for wellness
This research uses video recordings, as well as contact measurements, in order to extract vital sign information, primarily heart rate variability, and to analyze it to infer wellness levels: body readiness, stress and fatigue levels, and diagnostic information. Techniques applied range from image processing to change point and anomaly detection. Our group’s interest ranges from consumer-level wellness solutions to security systems. Principal investigator: Vicky Ikonomidou.
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