In silico exploration of post-burn contraction using uncertainty quantification

More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 G. Egberts
Related content
Research Group
Numerical Analysis
ISBN (print)
978-94-6384-463-5
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Burns can make patients’ lives quite miserable. Apart from prominent and thickened, or hypertrophic, scars, the skin may be characterized by contraction. When this contraction is so severe that the patient loses joint mobility, it is called contracture. Then a patient may have difficulties with sports or other daily activities. The consequence can be an enormous psychosocial burden for the patient. Understanding contraction mechanisms is essential to improve and optimize the treatment of contractures. This understanding can arise from clinical (in vivo) and experimental (in vitro) observations but can also be explored using mathematical models (in silico). Mathematical models describe quantitative relations and can explain specific trends and make predictions. Further, in silico models forman alternative for animal experiments. One such mathematical model is the Biomorphoelastic model for post-burn contraction [1]. This model arises from conservation laws expressed in partial differential equations on a continuous (macro) scale. We study this model’s one- and twodimensional counterparts...

Files

Dissertation_Egberts.pdf
(pdf | 12.9 Mb)
- Embargo expired in 18-09-2023
License info not available