Adaptive Biofeedback-Driven Gamified Therapy in XR for Mental Health Support

About the Project

This project proposes the development of an adaptive, gamified therapeutic platform using Extended Reality (XR) to support mental health interventions. The focus is on integrating real-time biofeedback, augmented reality (AR), and game-based therapeutic tasks into a clinically-informed digital experience. By aligning gameplay with therapeutic goals such as emotional regulation, exposure therapy, and cognitive behavioural strategies, the system will offer a personalised, evidence-based mental health support tool for both independent use and therapist-guided sessions.

Mental health care faces challenges in accessibility, engagement, and personalisation. Traditional therapeutic approaches often lack continuity outside the clinic, while many digital tools offer limited adaptability or clinical oversight. Recent advances in XR, wearable biofeedback devices, and serious game design allow for the creation of immersive systems that can reflect emotional states, reinforce positive coping strategies, and provide consistent therapeutic engagement across settings. This project addresses the opportunity to design a responsive, emotionally intelligent therapeutic XR platform that supports both patients and clinicians.

Candidates should have appropriate academic qualifications (first or upper second class honours, and preferably MSc) in Game Design, Computer Science, User Experience, Biomedical Engineering, Psychology or Cognitive Science, or other relevant area, strong background in programming, and desire to become experts in Digital Rehabilitation and Extended Realities.

Funding Notes

there is no funding for this project

References

• Nagy, B., Prieto, E.H., Mirza, A., Johnson, G., Usman, M.A., Smith, C., Francik, J., Bakirtzis, C., Politis, C. and Grigoriadis, N., 2025, January. Therapy reloaded: mixed reality games for hand rehabilitation. In 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC) (pp. 1-6). IEEE.
• Johnson, G., Mirza, A., Usman, M.A., Sharp, N., Smith, C., Francik, J., Bakirtzis, C., Politis, C. and Grigoriadis, N., 2024, August. Therapy reloaded: Temporal neural network-based platform for processing muscle activity measurement in electromyography-games. In 2024 IEEE 12th International Conference on Serious Games and Applications for Health (SeGAH) (pp. 1-8).