Semester / Bachelor / Master thesis: “The biomechanics of human body during balance on a wobble board and gait perturbed” (70% experimental, 30% theoretical)
06.12., Student assistants, internships, student research projects
Maintaining joint stability and balance is key for human movement, yet current datasets rarely combine EMG, GRF, and MoCap, limiting biomechanical modeling. This thesis will collect a high-quality multimodal dataset capturing muscle co-contraction during wobble-board balancing and controlled gait perturbations, providing a strong basis for future work, including machine learning models of neuromuscular responses.
Research objectives
The main goal of this thesis is to use the ethically approved experimental protocol, collect a multi-modal dataset and perform a primary analysis on it. The dataset integrates:
1. EMG: measuring muscle activation.
2. MoCap: tracking whole-body kinematics.
3. GRF: capturing the external forces acting on the body.
Methodology
4. Literature review: study state-of-the-art methods in balancing on a balance board, gait perturbation and muscle co-contraction analysis.
5. Participants recruitment: searching for male and female participants willing to perform the balance or the gait protocol.
6. Data collection: preparing the participants for performing the protocol, ensuring safety and consistency.
7. Data analysis: to be defined together with the student.
Expected outcomes
8. A well-structured multimodal dataset of balancing on a wobble board and walking under perturbations.
9. Analysis targets: to be defined together with the student.
Requirements
10. Strong interest in experimental research.
11. Background in mechanics, biomechanics, sports science, biomedical engineering, or a related field.
12. Experience with EMG, motion capture, or force plate data collection is a plus.
13. Basic knowledge of signal processing, Python, OpenSim or machine learning is a plus.
We offer
14. Access to the Rehabilitation Robotics Lab of MIRMI, TUM.
15. Supervision and support from leading researchers in gait analysis.
16. Hands-on experience with cutting-edge motion analysis technologies.
17. Potential to contribute to high-impact scientific publications.
Application
Interested candidates should submit:
18. A CV (max. 2 pages).
19. Transcript of records.