This project developed AI Care, a voice-based caregiving system for people with early-stage Alzheimer's disease. Unlike conventional voice assistants, it uses caregiver-maintained medical records to provide personalised, safety-aware support. By adapting to users rather than requiring users to adapt to technology, AI Care aims to extend safe, independent living at home.

This research develops advanced brain-machine interface systems to improve life for spinal cord injury patients. Using neural networks such as FinNet and dynamic recurrent neural decoders, the work aims to better extract and translate brain activity into movement while creating low-power hardware capable of supporting long-term practical neuroprosthetic applications.

This research explores how generative AI can create personalized reading materials based on autistic children’s special interests. Using AI-generated stories tailored to individual passions, the study examines effects on engagement and story retelling, suggesting that personalized, strength-based educational tools may improve reading experiences and accessibility for neurodivergent learners.

This research addresses password accessibility challenges for people with vision impairment. It examines current difficulties and introduces “bend passwords,” a tactile input method using flexible devices. Early findings suggest they are secure and memorable. The work aims to develop inclusive authentication systems that improve digital security and usability for visually impaired users.

This research introduces “Countmarks,” an ergonomic interaction method for smart glasses using multi-finger gestures on a smartphone. It offers a faster, more accurate, and private alternative to controllers, voice commands, and mid-air gestures. The system improves usability, accessibility, and safety, particularly in real-world contexts like walking or driving.

This research explores how wearable technology can improve video game accessibility for players with upper limb disabilities. Through interviews, it develops design guidelines emphasizing flexibility, independence, and modularity. The project aims to build and test prototypes, advancing inclusive gaming design and ensuring disabled players are better represented in interactive technology development.

This research shows that children born without a hand can generate complex muscle signals by imagining movements, enabling control of advanced prosthetics. Their abilities develop similarly to typical motor patterns, challenging assumptions and expanding access to sophisticated prosthetic technology for paediatric patients.

his research develops a classification system for wheelchair navigation based on surface difficulty, inspired by ski trail ratings. By measuring vibration and effort across urban environments, it aims to provide users with actionable information to support safer route choices, reduce injury risk, and improve independence and accessibility in everyday mobility.

This research develops digital twin systems to personalise robotic exoskeleton movement. By integrating biomechanical modelling with real-time robotic control, it enables adaptive, user-specific walking patterns. The approach aims to improve rehabilitation outcomes by making assistive devices more natural, responsive, and aligned with individual movement needs.

This research investigates the use of Bee-Bot, a programmable robot, to support children with autism. Structured robot-based activities aim to improve communication, social interaction, and purposeful play, while incorporating parent and teacher perspectives to assess long-term developmental and behavioral benefits.