This research explores exergames that combine gaming and exercise to improve fitness. By integrating adaptive difficulty, full-body motion, and narrative storytelling, it aims to create experiences that are both engaging and physically effective. The goal is to motivate sustained exercise by making workouts enjoyable and personalized through game design.

This research uses wearable data and AI to detect disease earlier by analyzing continuous health signals rather than isolated clinical snapshots. By personalizing models to individual baselines, the system identifies subtle changes linked to conditions like infections, heart issues, and mental health crises, enabling earlier intervention and potentially saving lives.

This research applies the concept of hormesis—where low doses are beneficial but high doses harmful—to pornography use. Since excessive porn use is associated with mental-health problems, the project seeks to identify the “healthy limit” of use. Participants will complete daily smartphone surveys over a month, allowing the researcher to model how porn consumption affects well-being and how moral beliefs modify these effects. The goal is to build a personalised app that guides individuals toward safe levels of use and reduces polarisation in debates about pornography.

Digital health expanded during COVID-19, but many services exclude people seeking support for alcohol and drug use. This research uses inclusive design, interviews, and workshops with people with lived experience to identify barriers, reduce stigma, improve usability, and guide industry toward creating accessible, equitable digital care for all.

This PhD developed a remote postoperative wound-monitoring pathway to replace dangerous, costly hospital journeys for patients in low-resource settings. Using a culturally adaptable questionnaire and phone/video follow-up, the method proved feasible, reliable, accurate, economical, and scalable. It could save the NHS £500 million annually while improving global surgical safety.