Semester / Bachelor / Master thesis: “The biomechanics of human body during balance on a wobble board and gait perturbed” (70% experimental, 30% theoretical)
06.12., Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten
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.