Prof. Dr. Anne Koelewijn
Junior Professorship for Computational Movement Science
Carl-Thiersch-Straße 2b
91052 Erlangen
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik
Carl-Thiersch-Straße 2b
91052 Erlangen
- Phone number: +49 9131 85-20296
- Email: anne.koelewijn@fau.de
- Website: https://www.mad.tf.fau.de/person/anne-koelewijn/
I currently lead the “Biomechanical Motion Analysis and Creation (BioMAC)” group.
Humans are the most fascinating machines in the world. Their efficiency of movement is unmatched by other bipedals while their control system is noisy and redundant and their actuators (muscles) are not that efficient at all. I think that once we understand why we walk the way we do, we can greatly advance technologies such as robotics and prosthetics and orthotics, as well as improve other human movements in for example sports.
Find me on social media: Twitter | Google Scholar | ResearchGate | LinkedIn
- Since 08/2019
Junior Professorship for Computational Movement Science (Endowed by adidas) at the FAU - 2018 – 2019
Postdoc at BIOROB, the biorobotics lab at EPFL - 2014 – 2018
D.Eng. student in the Parker Hannifin Laboratory for Human Motion and Control, Cleveland State University
Supervisor: Dr. Antonie J. van den Bogert - 2011 – 2014
MSc. Mechanical Engineering, specialization Biomechanical Design, Delft University of Technology - 2008 – 2011
BSc. Aerospace Engineering, Delft University of Technology
Please visit the lab’s project overview
2021
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BASH: Biomechanical Animated Skinned Human for Visualization of Kinematics and Muscle Activity
16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Online, 8. February 2021 - 10. February 2021)
In: Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP 2021
DOI: 10.5220/0010210600250036
URL: https://www.scitepress.org/PublicationsDetail.aspx?ID=qmYWslU7yL0=&t=1
BibTeX: Download
2020
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CNN-Based Estimation of Sagittal Plane Walking and Running Biomechanics From Measured and Simulated Inertial Sensor Data
In: Frontiers in Bioengineering and Biotechnology 8 (2020), p. 1-14
ISSN: 2296-4185
DOI: 10.3389/fbioe.2020.00604
BibTeX: Download - , :
Exploring the Contribution of Proprioceptive Reflexes to Balance Control in Perturbed Standing
In: Frontiers in Bioengineering and Biotechnology 8 (2020)
ISSN: 2296-4185
DOI: 10.3389/fbioe.2020.00866
URL: https://www.frontiersin.org/articles/10.3389/fbioe.2020.00866/abstract
BibTeX: Download - , :
A solution method for predictive simulations in a stochastic environment
In: Journal of Biomechanics (2020), Article No.: 109759
ISSN: 0021-9290
DOI: 10.1016/j.jbiomech.2020.109759
BibTeX: Download - , , , , , , :
Efficient trajectory optimization for curved running using a 3D musculoskeletal model with implicit dynamics
In: Scientific Reports (2020), Article No.: 17655
ISSN: 2045-2322
DOI: 10.1038/s41598-020-73856-w
URL: https://www.nature.com/articles/s41598-020-73856-w
BibTeX: Download
2019
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Metabolic cost calculations of gait using musculoskeletal energy models, a comparison study
In: PLoS ONE 14 (2019), Article No.: e0222037
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0222037
BibTeX: Download - , , , , , :
Turning a corner in predictive musculoskeletal simulations of gait using implicit dynamics
Dynamic Walking 2019 (Canmore, Alberta, 3. June 2019 - 6. June 2019)
In: 14th Annual Dynamic Walking Conference 2019 2019
URL: https://www.mad.tf.fau.de/files/2019/05/Nitschke_Dynamic_Walking.pdf
BibTeX: Download
2018
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A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait
In: Computer Methods in Biomechanics and Biomedical Engineering 21 (2018), p. 521 - 531
ISSN: 1025-5842
DOI: 10.1080/10255842.2018.1490954
BibTeX: Download
2016
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Joint contact forces can be reduced by improving joint moment symmetry in below-knee amputee gait simulations
In: Gait & Posture 49 (2016), p. 219 - 225
ISSN: 0966-6362
URL: https://www.sciencedirect.com/science/article/abs/pii/S0966636216301448
BibTeX: Download
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