Anterior cruciate ligament (ACL) injuries often lead to long-term impairments and require careful monitoring of movement quality during rehabilitation. Traditional motion analysis tools are costly and impractical outside labs. This thesis aimed to develop a simple and clinically applicable tool to assess both kinematics and kinetics. Initial testing of inertial sensors proved insufficient for dynamic tasks. A markerless approach using a smartphone camera and OpenPifPaf showed promising accuracy for joint kinematics and performance metrics during hops, balance tasks, and running. A simplified 2D multibody model estimated ground reaction forces with good agreement to reference data, though torque prediction remained challenging. All developments were integrated into a user-friendly software. While validated on healthy subjects in 2D, the tool lays the groundwork for accessible motion assessment in clinical settings and shows potential for future application in ACL-injured populations.
Lambricht, N. (2025). Movement quality assessment using lightweight motion capture systems : toward field-ready tools for ACL-related functional evaluation. https://hdl.handle.net/2078.5/248931