Research Overview
During my master’s dissertation, I explored the potential of Machine Learning in identifying connections between immersion in multimedia content and physiological signals, primarily focusing on electroencephalogram (EEG) data.
Main Contributions
Objective condition classification: The study showed that EEG data can effectively distinguish between cases where users watch content in objectively different settings.
Subjective rating classification: The research also revealed that EEG data can accurately predict when a user will rate an experience as immersive.
Implications
My master’s thesis emphasizes the feasibility of modeling cognitive processes such as immersion using EEGs. These findings could enable personalized immersive experiences in emerging multimedia formats and have implications for various industries, including entertainment, healthcare, and education.
Acknowledgements
I want to thank the researchers at Ghent University who helped me during my master’s dissertation: Prof. dr. ir. Maria Torres Vega, Ir. Sam Van Damme, Ir. Mohammad Javad Sameri and Prof. dr. ir. Filip De Turck. I’d also like to express my gratitude to Dr. Anne-Flore Perrin for the data and prior research in the field of quality assessment of immersive media.