Thesis Project Form

Lower-limb prostheses require control strategies that can adapt to the user’s movement intention and to changing locomotion conditions. Surface electromyography is commonly investigated for myoelectric control, but it can be affected by noise, electrode placement and signal variability. Ultrasound imaging may provide complementary information on muscle morphology and tissue motion. This thesis investigates whether ultrasound-derived muscle features can be considered as candidate control signals for future lower-limb prosthetic applications.

The project aims to extract and compare neuromuscular, morphological, kinematic and kinetic signals during walking at different speeds. The main activities include definition of an experimental pipeline, multimodal data synchronization and processing, muscle fascicle tracking, optical-flow analysis, gait-cycle segmentation, feature extraction and comparisons across speeds and participants.

The project provides training in experimental gait analysis, ultrasound and EMG processing, motion capture, multimodal synchronization, MATLAB programming, optical flow and OpenSim musculoskeletal modelling. It also develops skills in signal processing, data visualization and interpretation of biomechanical results.