Datasets and Software
Open science
We are committed to open science and collaborative progress. Wherever possible, we make the data we collect publicly available to support transparency, reproducibility, and further discovery. All shared data are fully anonymized, meaning that individuals who volunteer in our research cannot be identified from the data.
The musculoskeletal models we develop are shared openly, enabling other researchers to use, test, and build upon them. In addition, we create and distribute open software tools designed to be accessible and usable by researchers. By sharing data, models, and tools, we aim to accelerate innovation and foster a global research community.
Age-related Compensation Strategies
Data Application 2022 – Sit-to-walk data analysis (50 participants)
Experimental Data
Complementary to the article ‘Why do older adults stand-up differently to young adults?: Investigation of compensatory movement strategies in sit-to-walk.‘: Click here , we have published the data and analysis in a stand-alone application accessible
Neuromuscular Controller
2D sit-to-walk controller
Simulation Data
Complementary to the article: van der Kruk, E., & Geijtenbeek, T. (2024). A planar neuromuscular controller to simulate compensation strategies in the sit-to-walk movement. PLoS one, 19(6), e0305328. article
Case Study Unilateral Knee Pain
2D sit-to-walk
Simulation Data
Complementary to the article: Van Der Kruk, E., & Geijtenbeek, T. (2024). Is increased trunk flexion in standing up related to muscle weakness or pain avoidance in individuals with unilateral knee pain; a simulation study. Frontiers in Bioengineering and Biotechnology, 12, 1346365. article
Overview Accuracy Motion Capture Systems
Webpage
This platform is part of the open-access article Accuracy of human motion capture systems for sport applications; state-of-the-art review of the European Journal of Sport Sciences.
Portable Balance Lab
Educational Course
Course Material