It is my goal to improve movement for people, e.g. those with a disability or athlete. To do so, I aim to better understand human motion, and design better devices, such as prostheses, exoskeletons, and running shoes, as well as prevent injuries, such as knee osteoarthritis. I focus on wearable technologies and the combination of physics-based models with machine learning methods.
Research projects
Personalized musculoskeletal models and gait simulations: using imaging techniques such as diffusion tensor imaging (DTI), as well as using machine learning methods, we aim to personalize musculoskeletal models and gait simulations, such that we can per
Biomechanical Assessment and Simulation
(Third Party Funds Single)
Term: 1. August 2019 - 1. August 2022 Funding source: Industrie
The goal of this project is to develop data-based and knowledge-based methods for accurate analysis and simulation of human motion, focused on gait. Movement simulations are created by solving trajectory optimization problems, using an objective related to energy, a musculoskeletal model to model the body and muscle dynamics, and constraints to define the movement task. We use data-based approaches to improve musculoskeletal models and simulation accuracy. With our research, we aim to better understand human motion, and thereby improve design of wearables, such as prostheses, exoskeletons, and running shoes.
Koelewijn, A., & Selinger, J.C. (2022). Predictive Gait Simulations of Human Energy Optimization. In Juan C. Moreno, Jawad Masood, Urs Schneider, Christophe Maufroy, Jose L. Pons (Eds.), Wearable Robotics: Challenges and Trends. (pp. 377-381). Cham: Springer Science and Business Media Deutschland GmbH.
Schleicher, R., Nitschke, M., Martschinke, J., Stamminger, M., Eskofier, B., Klucken, J., & Koelewijn, A. (2021). BASH: Biomechanical Animated Skinned Human for Visualization of Kinematics and Muscle Activity. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP (pp. 25-36). Online.
It is my goal to improve movement for people, e.g. those with a disability or athlete. To do so, I aim to better understand human motion, and design better devices, such as prostheses, exoskeletons, and running shoes, as well as prevent injuries, such as knee osteoarthritis. I focus on wearable technologies and the combination of physics-based models with machine learning methods.
Research projects
Personalized musculoskeletal models and gait simulations: using imaging techniques such as diffusion tensor imaging (DTI), as well as using machine learning methods, we aim to personalize musculoskeletal models and gait simulations, such that we can per
Biomechanical Assessment and Simulation
(Third Party Funds Single)
Funding source: Industrie
The goal of this project is to develop data-based and knowledge-based methods for accurate analysis and simulation of human motion, focused on gait. Movement simulations are created by solving trajectory optimization problems, using an objective related to energy, a musculoskeletal model to model the body and muscle dynamics, and constraints to define the movement task. We use data-based approaches to improve musculoskeletal models and simulation accuracy. With our research, we aim to better understand human motion, and thereby improve design of wearables, such as prostheses, exoskeletons, and running shoes.
2022
2021
2020
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