John Henry Programme Leader, Games Design

John Henry

I am a Senior Lecturer and the BSc Games Design Programme Leader at Manchester Metropolitan University with research interests in the combination of game experiences with the sensor technology and the Internet of Things.

My research background includes developing simulations for raising awareness and measuring student engagement at the university level of study through a Serious Game that embedded the Internet of Things. My PhD produced a development framework, allowing technology for good to develop projects that combine Serious Games and the Internet of Things. Current research projects are investigating the use of Serious Games for mental wellbeing and the use of wearable technology as game input.

LinkedIn: https://www.linkedin.com/in/drjohnhenry

Twitter: @dr_johnhenry

I have worked on multiple research projects that aided Games to the Web and utilised Web Technologies to make more impactful Serious Game, including web integration of telerehabilitation systems and web integration of training system that illustrates BPMN in 3D.

I am actively researching using biofeedback to measure anxiety for altering virtual rehabilitation experiences in real-time. For further information, please see my OCRID, Google Scholar and ReseachGate profile links below.

Google Scholar: ‪John Henry – ‪Google Scholar

OCRID: https://orcid.org/0000-0003-3674-8208

ResearchGate: John Henry (researchgate.net)

Notable Publications

Henry, J., Tang, S., Mukhopadhyay, S. and Yap, M.H., 2021. A randomised control trial for measuring student engagement through the Internet of Things and serious games. Internet of Things13, p.100332.

Melthis, J., Tang, S., Yang, P., Hanneghan, M. and Carter, C., 2016. Topologies for combining the internet of things and serious games. Journal of Intelligent & Fuzzy Systems31(5), pp.2685-2696.

Henry, J., Tang, S., Hanneghan, M. and Carter, C., 2018, May. A framework for the integration of serious games and the Internet of Things (IoT). In 2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH) (pp. 1-8). IEEE.

Henry, J., Lloyd, H., Turner, M. and Kendrick, C., 2023. On the robustness of machine learning models for stress and anxiety recognition from heart activity signals. IEEE Sensors Journal.