ABSTRACT: The use of integrated 3D motion capture is currently well-accepted to study musculoskeletal disorders and evaluate the impact of treatments, mainly in a research context. Combining experimental data with modeling and dynamic simulation approaches, we now have access to parameters which today cannot be measured non-invasively. In the research field on degenerative joint disease, there is the ambition and proof of concept to use these techniques to contribute to patient stratification and consequent prescription of targeted rehabilitation strategies. Likewise, the potential in defining effective treatment approaches to study gait dysfunction in children with CP is becoming more and more accepted. In these research applications, high fidelity data from medical imaging techniques and 3D motion capture systems are abundantly used to personalize complex musculoskeletal models and high-fidelity input data. However, when bridging into the clinical decision-making workflow, there are dedicated challenges that merely lie in the sparse data sets and the need to simplify the modeling workflows without losing important patient-specific features.


BIO: From her PhD (2000) onwards, Ilse Jonkers successfully bridged from a classical human movement science and physical therapy profile towards an integrated biomedical science and biomedical engineering profile, exploiting maximally the use of 3D motion capture and multi-body simulation techniques to advance the understanding on pathological movement. The two-year postdoctoral stay at the bioengineering department at Stanford University (Prof Delp) was a pivotal experience in this process. To date, she is a professor at the Human Movement Biomechanics Research Group and affiliated with the Tissue Homeostasis and Disease Laboratory at KU Leuven.

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