Digital Twin Modeling of Human Thorax for HFCC Therapy Using COMSOL Multiphysics®
Patients with muco-obstructive airway diseases, such as cystic fibrosis, rely on daily therapies to help clear their airways. High-frequency chest compression (HFCC) devices offer a home-based solution, but variations in operating frequency raise concerns about treatment consistency and effectiveness.
In this webinar, Arife Uzundurukan, a postdoctoral fellow at Polytechnique Montreal, will demonstrate how the COMSOL Multiphysics® software was used to develop a computed tomography-based finite element model (CT-FEM) for predicting thoracic vibratory responses across HFCC operating frequencies (5–100 Hz). The presentation will explore how lung behavior was simulated using Biot’s theory, under both normal and pathological conditions.
A detailed multi-organ thoracic model — including the lungs, ribcage, trachea, and soft tissues — was created as a digital twin using a sequential workflow involving four different software platforms. The HFCC device itself was modeled as an acoustic pressure source.
Results reveal that the frequency response function (FRF) peaks observed in the model align closely with findings from three independent experimental studies. Notably, changes in alveolar radius significantly influence wave velocity and energy density within the lungs, without substantially altering the thorax’s overall FRF.
Attend this live webinar to see how this study advances CT-FEM methodology for multi-organ simulations and deepens our understanding of low-frequency thoracic resonance. You will also get a look at how COMSOL Multiphysics® is vital for biomedical and vibroacoustic modeling of human thorax digital twins.
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- Starts 16 July 2025 12:00 PM UTC
- Ends 24 July 2025 07:00 PM UTC
- No Admission Charge
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Digital Twin Modeling of Human Thorax for HFCC Therapy Using COMSOL Multiphysics®
Patients with muco-obstructive airway diseases, such as cystic fibrosis, rely on daily therapies to clear their airways. High-frequency chest compression (HFCC) devices offer home-based treatments, but inconsistencies in operating frequencies raise concerns about their effectiveness. This study uses COMSOL Multiphysics® to develop a computed tomography-based finite element model (CT-FEM) to predict thoracic vibratory responses across HFCC operating frequencies (5–100 Hz). A detailed multi-organ thoracic model, including the lungs, ribcage, trachea, and soft tissues, was generated as a digital twin through a sequential workflow across four software platforms, with the HFCC device modeled as an acoustic pressure source. Lung behavior was simulated using Biot’s theory under normal and pathological conditions. Investigated frequency response function (FRF) peaks are consistent with three independent experimental studies. Changes in alveolar radius significantly impact wave velocity and energy density inside the lungs, rather than altering the FRF of the thorax. This study advances CT-FEM methodology for multi-organ simulation, enhances understanding low-frequency thoracic resonance, and highlights COMSOL Multiphysics® as a critical tool for biomedical and vibroacoustic modeling of human thorax digital twins.
Biography:
Arife Uzundurukan holds a double B.Sc. in Mechanical and Energy Systems Engineering from Atilim University (2016), an M.Sc. from Gazi University (2019), and a Ph.D. from the University of Sherbrooke (2024), where she developed a CT-based finite element model (CT-FEM) for biomedical device design. She is a globally recognized specialist in numerical modeling with COMSOL Multiphysics, winning over 10 awards for research and leadership. Dr. Uzundurukan investigated bone ultrasound and delivered a seminar titled "COMSOL Multiphysics® as an Assistant: From Lecture to Thesis and Career Development" as a Postdoctoral Fellow at Polytechnique Montreal. Currently, she is a FRQ-funded B3X Postdoctoral Fellow at McGill University and also serves as Treasurer of the IEEE Montreal Section. Outside academia, she is passionate about volunteering for children's events. More details: LinkedIn (https://www.linkedin.com/in/arife-uzundurukan/).
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