Computer Modeling of Cardiovascular System

Our lab is developing digital twins of the cardiovascular system through advanced computational modeling. These digital twins aim to simulate and predict cardiovascular signals and parameters across various conditions, facilitating the creation of innovative diagnostic methods and the personalization of treatments.

Objective

Develop digital twins of the human thorax to facilitate the design, testing, and validation of innovative diagnostic and therapeutic methods for a wide range of cardiovascular conditions

Researchers

Amirtahà Taebi

PI

Current members involved:

Skillsets

Finite element modeling
Computational fluid dynamics modeling
Machine learning

Sponsors

Study Workflow

1) CFD-FEA simulations to predict sound and vibration propagation through body 2) in-vitro and in-vivo measurements to validate simulations 3) analysis of the signals using state-of-the-art signal processing and machine learning. © TaebiLab

Study Workflow

1) CFD-FEA simulations to predict sound and vibration propagation through body 2) in-vitro and in-vivo measurements to validate simulations 3) analysis of the signals using state-of-the-art signal processing and machine learning. © TaebiLab

1/1

Publications

Monfared, M., Gamage, P.T., Taebi, A. (2024). Investigating Seismocardiogram Patterns: A Computational Modeling of Cardiac Wall Motion Propagation to the Chest Surface. 2024 ASME International Mechanical Engineering Congress and Exposition, Portland, OR.

doi (not available yet)

Full list of publications in Google Scholar