Thesis Project Form

Many activities of daily living require coordinated motion of both arms, posing significant challenges for individuals with orthopedic or neurological conditions that impair motor control in one arm. Robot-mediated rehabilitation offers potential solutions for restoring lost motor control. Techniques like mirroring leverage the residual functionality of the intact limb to guide the movement of the impaired one - for instance, through an exoskeleton.

The general objective is to develop and implement a mirror controller for an upper limb exoskeleton. The student will be responsible for acquiring a dataset that includes IMU and exoskeleton data recorded during experimental sessions with healthy subjects wearing the exoskeleton. This dataset will be exploited to analyse and describe the correlation between IMU data and the corresponding robotic configurations. The student will integrate Inertial Measurement Units (IMUs) into a unified sensor platform (Unity & MuJoCo) to estimate the movements of one upper limb. This information will then be used to control the FloatEVO Exoskeleton to assist the movements of the impaired arm.
The control scheme will first be tested in simulation and, if feasible, directly on the exoskeleton. The goal is to extract the control signals that enable the exoskeleton to replicate the movements of the subject's healthy arm.

IMU-based motion capture
Control of exoskeletons
Simulation and control of musculoskeletal systems
Sensors integration
Communication protocols
Machine Learning models