This thesis investigates visual perception across real-world and digital environments
through an interdisciplinary approach that integrates neuroscience,
psychology, mathematics, and immersive technology. It begins by outlining the
fundamental science of light and vision, followed by a review of contemporary research
on reading and visual perception. The thesis then examines signal processing
techniques commonly applied to electroencephalography (EEG), addressing
both their mathematical foundations and practical implementation for analysing
non-stationary neural signals.
Building on this framework, a generalised EEG analysis pipeline integrating
established time–frequency and spatial filtering methods is developed and
validated using a public motor imagery dataset. The validated pipeline is subsequently
applied to analyse behavioural and EEG data from a visual perception
experiment comparing stimulus presentation across real-world, two-dimensional
screen-based, augmented reality, and virtual reality environments. Reaction time
measures are used to assess perceptual efficiency, while EEG recordings provide
insight into associated neural dynamics.
The thesis concludes with an exploratory investigation of visual stress through
a behavioural case study on Irlen Syndrome, examining how digital colour filtering
may influence reaction time under varying task demands. Although constrained
by sample size, the work demonstrates the feasibility of combining EEG,
behavioural measures, and immersive technologies to study visual perception.
Overall, this thesis contributes methodological tools and preliminary empirical
insights that inform future research on visual processing in modern, technologymediated
environments.
