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Cardiovascular modeling of a digital twin for hybrid mock loop testing
The main goal of this thesis is to use advanced parameter estimation techniques for creation of a digital twin of the cardiovascular system.
As cardiovascular disease continue to be the leading cause of mortality worldwide. Computational and hybrid testing of treatment strategies such as heart pumps presents a promising avenue for saving lives. However, these models are most often generic and lack patient-specific properties. This thesis aims to enable automatic tuning of a cardiovascular model to a digital twin. In a first step, this will include improving the accuracy and performance of a cardiovascular model by validating its function against the state-of-the-art. In a second step, the candidate will also be responsible in developing a parameter tuning algorithm for in order to match the numerical results to specific patient-case scenario.
As cardiovascular disease continue to be the leading cause of mortality worldwide. Computational and hybrid testing of treatment strategies such as heart pumps presents a promising avenue for saving lives. However, these models are most often generic and lack patient-specific properties. This thesis aims to enable automatic tuning of a cardiovascular model to a digital twin. In a first step, this will include improving the accuracy and performance of a cardiovascular model by validating its function against the state-of-the-art. In a second step, the candidate will also be responsible in developing a parameter tuning algorithm for in order to match the numerical results to specific patient-case scenario.
- Familiarize yourself with the numerical model of the cardiovascular system’s functioning.
- Validate the MATLAB model against the Aplysia software
- Estimate parameters for specific patient scenarios using numerical optimization techniques
- Explore multi-objective optimizers to improve accuracy
- Write a report summarizing the project’s findings and conclusions.
- Familiarize yourself with the numerical model of the cardiovascular system’s functioning. - Validate the MATLAB model against the Aplysia software - Estimate parameters for specific patient scenarios using numerical optimization techniques - Explore multi-objective optimizers to improve accuracy - Write a report summarizing the project’s findings and conclusions.
Experienced parameters/system identification techniques or optimization Interested in detailed model implementation and validation Eager to engage in a cultural research exchange experience Highly Motivated and independent
The chair of Product Development
and Engineering Design at the
ETH Zurich considers itself a center
for system-oriented product
development and innovation. The group at KTH in Stockholm, Sweden, focuses on sensor systems and medical devices to predict, prevent, and cure cardiovascular diseases. The purpose of this master thesis is to foster collaboration between the pd|z at ETH Zurich and the Department of Biomedical Engineering at KTH Royal Institute of Technology.
The chair of Product Development and Engineering Design at the ETH Zurich considers itself a center for system-oriented product development and innovation. The group at KTH in Stockholm, Sweden, focuses on sensor systems and medical devices to predict, prevent, and cure cardiovascular diseases. The purpose of this master thesis is to foster collaboration between the pd|z at ETH Zurich and the Department of Biomedical Engineering at KTH Royal Institute of Technology.
6 months Master Thesis Systems, Robotics, Control Engineering
Emanuele Perra (Thesis supervisor)
emaper@kth.se
Seraina Dual (Ass. Prof.)
seraina@kth.se
KTH Royal Institute of Technology
Stockholm, Sweden
Emanuele Perra (Thesis supervisor) emaper@kth.se Seraina Dual (Ass. Prof.) seraina@kth.se KTH Royal Institute of Technology Stockholm, Sweden