Funding tool: Dissertations
Project-ID: FTI22-D-030
Project start: 01. Jänner 2024
Project end: 31. Dezember 2026
Runtime: 36 months / ongoing
Funding amount: ca. € 71.000,00

Brief summary:
The objective of this PhD project is to improve the applicability and trustworthiness of using machine learning methods in gait analysis. For this purpose, "Explainable Artificial Intelligence" (XAI) methods will be used to better explain the complex results of musculoskeletal simulations for clinical use. During this project, XAI methods will be adapted, optimized and further developed to provide meaningful results for gait analysis. Ultimately, clinicians should be able to understand why a model arrives at its predictions, which may also lead to new insights into disease patterns and new treatment options for musculoskeletal disorders. To best adapt the results of the methods to clinical practice, a qualitative evaluation will also be conducted to determine which type of visualization is most informative for clinicians.

Keywords:
Muskoskelettal Modelling, Gait Analysis, Machine learning, Explainable AI