Limitations of time-delayed case isolation in heterogeneous SIR models
(2022) American Control Conference, 2022 2022. p.2994-2999- 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 classic Windkessel... (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/f1586e9e-0f3b-4b50-bd83-24777b885498
- author
- Hansson, Jonas LU ; Govaert, Alain LU ; Pates, Richard LU ; Tegling, Emma LU and Soltesz, Kristian LU
- organization
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- American Control Conference
- volume
- 2022
- pages
- 2994 - 2999
- conference name
- American Control Conference, 2022
- conference location
- GA, United States
- conference dates
- 2022-06-08 - 2022-06-10
- external identifiers
-
- scopus:85138490998
- DOI
- 10.23919/ACC53348.2022.9867465
- project
- COVID-19: Dynamical modelling for estimation and prediction
- language
- English
- LU publication?
- yes
- id
- f1586e9e-0f3b-4b50-bd83-24777b885498
- alternative location
- https://arxiv.org/abs/2209.09186
- date added to LUP
- 2022-03-04 14:48:18
- date last changed
- 2023-12-01 11:24:41
@inproceedings{f1586e9e-0f3b-4b50-bd83-24777b885498, 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 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 = {{Hansson, Jonas and Govaert, Alain and Pates, Richard and Tegling, Emma and Soltesz, Kristian}}, booktitle = {{American Control Conference}}, language = {{eng}}, pages = {{2994--2999}}, title = {{Limitations of time-delayed case isolation in heterogeneous SIR models}}, url = {{http://dx.doi.org/10.23919/ACC53348.2022.9867465}}, doi = {{10.23919/ACC53348.2022.9867465}}, volume = {{2022}}, year = {{2022}}, }