Balanced Neuroprosthetic Assistance
IEEE TBME, 2026Striking a balance between user preference and biomechanical assistance with lower limb neuroprostheses.
A selection of lab members' research is available here.
Striking a balance between user preference and biomechanical assistance with lower limb neuroprostheses.
Optimising motor and gear topologies for performant, lightweight ankle exoskeletons.
Automatically identifying muscles from their electrical activity for precision functional electrical stimulation.
Examining the effects of sensory feedback and continuous control on prosthetic hand users.
Designing modular, non-humanoid end effectors for dramatically improved task performance.
Designing a short-range telehaptic exoskeleton to improve astronaut dexterity.
Adding immersive force feedback for safer and more efficient policies with imitation learning.
Developing an immersive virtual reality platform for pre-prosthetic hand training.
Utilising probabilistic distance metrics to achieve one-shot myoelectric control.
Using deep learning for myoelectric prosthetic hand control with embedded computation.
Developing a modular feedback armband for force and position proprioception from prosthetic hands.