The differential-algebraic Windkessel model with power as input
Pigot, Harry LU
and Soltesz, Kristian
LU
(2022)
American Control Conference, 2022
p.3006-3011
- Abstract
- The lack of methods to evaluate mechanical function of donated hearts in the context of transplantation imposes large precautionary margins, translating into a low utilization rate of donor organs. This has spawned research into cyber-physical models constituting artificial afterloads (arterial trees), that can serve to evaluate the contractile capacity of the donor heart.
The Windkessel model is an established linear time-invariant afterload model, that researchers committed to creating a cyber-physical afterload have used as a template. With aortic volumetric flow as input and aortic pressure as output, it is not directly obvious how a Windkessel model will respond to changes in heart contractility.
We transform the... (More) - The lack of methods to evaluate mechanical function of donated hearts in the context of transplantation imposes large precautionary margins, translating into a low utilization rate of donor organs. This has spawned research into cyber-physical models constituting artificial afterloads (arterial trees), that can serve to evaluate the contractile capacity of the donor heart.
The Windkessel model is an established linear time-invariant afterload model, that researchers committed to creating a cyber-physical afterload have used as a template. With aortic volumetric flow as input and aortic pressure as output, it is not directly obvious how a Windkessel model will respond to changes in heart contractility.
We transform the classic Windkessel model to relate power, rather than flow, to pressure. This alters the model into a differential-algebraic equation, albeit one that is straightforward to simulate. We then propose a power signal model, that is based on pressure and flow measurements and optimal in a Bayesian sense within the class of C2 signals. Finally, we show how the proposed signal model can be used to create relevant simulation scenarios, and use this to illustrate why it is problematic to use the Windkessel model as a basis for designing a clinically relevant artificial afterload. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1f769e42-89b0-435e-9edf-4366b90977fa
- author
- Pigot, Harry
LU
and Soltesz, Kristian
LU
- organization
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Modelling and simulation, cardiac afterload, heart evaluation, differential-algebraic equation
- host publication
- 2022 American Control Conference (ACC)
- article number
- 2022
- pages
- 3006 - 3011
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- American Control Conference, 2022
- conference location
- GA, United States
- conference dates
- 2022-06-08 - 2022-06-10
- external identifiers
-
- scopus:85138495710
- DOI
- 10.23919/ACC53348.2022.9867889
- project
- Functional ex vivo heart evaluation
- Hemodynamic Stabilization
- language
- English
- LU publication?
- yes
- id
- 1f769e42-89b0-435e-9edf-4366b90977fa
- date added to LUP
- 2022-03-14 18:57:52
- date last changed
- 2024-05-02 12:51:37
@inproceedings{1f769e42-89b0-435e-9edf-4366b90977fa,
abstract = {{The lack of methods to evaluate mechanical function of donated hearts in the context of transplantation imposes large precautionary margins, translating into a low utilization rate of donor organs. This has spawned research into cyber-physical models constituting artificial afterloads (arterial trees), that can serve to evaluate the contractile capacity of the donor heart.<br/><br/>The Windkessel model is an established linear time-invariant afterload model, that researchers committed to creating a cyber-physical afterload have used as a template. With aortic volumetric flow as input and aortic pressure as output, it is not directly obvious how a Windkessel model will respond to changes in heart contractility.<br/><br/>We transform the classic Windkessel model to relate power, rather than flow, to pressure. This alters the model into a differential-algebraic equation, albeit one that is straightforward to simulate. We then propose a power signal model, that is based on pressure and flow measurements and optimal in a Bayesian sense within the class of C2 signals. Finally, we show how the proposed signal model can be used to create relevant simulation scenarios, and use this to illustrate why it is problematic to use the Windkessel model as a basis for designing a clinically relevant artificial afterload.}},
author = {{Pigot, Harry and Soltesz, Kristian}},
booktitle = {{2022 American Control Conference (ACC)}},
keywords = {{Modelling and simulation; cardiac afterload; heart evaluation; differential-algebraic equation}},
language = {{eng}},
pages = {{3006--3011}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{The differential-algebraic Windkessel model with power as input}},
url = {{https://lup.lub.lu.se/search/files/115310976/pigot2022differential.pdf}},
doi = {{10.23919/ACC53348.2022.9867889}},
year = {{2022}},
}