Computer Modeling of Cardiovascular System
twinHeart
(Digital Twins for Personalized Cardiovascular Health)
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.
© TaebiLab
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
Amirtahà Taebi
PI
Current members involved:
Skillsets
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Finite element modeling
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Computational fluid dynamics modeling
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Machine learning
Sponsors
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) 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
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, V004T06A006, Portland, OR.
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