Many stroke survivors face lasting gait impairments, and current robotic-assisted therapies, like exoskeletons, often rely on repetitive, pre-programmed movements, which can limit active engagement—a key to neural recovery. My PhD aims to make gait rehabilitation more adaptive and engaging by using AI to decode EEG signals that reveal a patient’s intentions (e.g., standing up or step length) and dynamically control an exoskeleton in response. During the project, I also intend to investigate how motor control adapts and reorganizes in response to training and how this process differs between healthy individuals and stroke patients.
Brain-computer interfaces
Computational modelling
Biosignal analysis and processing
Neuro-inspired Machine Learning
Brain Plasticity
Two years as a Research Assistant at the University of Bath. In the first year, contributed to developing an ear-based control method for assistive technology; in the second year, focused on computational modelling of electrical stimulation of sacral roots for bladder control.
MSc in Computational Neuroscience, Cognition and AI
BSc Molecular Bionics Engineering
Prof Damien Coyle
Prof Eamonn O’Neill
Dr Ben Metcalfe
