Blending Embodied Interactions Across Heterogeneous Contexts

Abstract

Blended realities–an emerging subset of mixed reality (MR) systems–enable embodied, non-verbal interaction across physically distributed environments by deliberately integrating physical and digital spaces to support co-presence and shared activity. However, differences in spatial layout and sociocultural norms can introduce perceptual distortions that lead to miscommunication. While prior work focuses on reducing spatial discrepancies, it often overlooks place-making and how people use space to construct roles and expectations.

To examine spatial and sociocultural dimensions together, I introduce a taxonomy of three interaction transmission modes: (1) transcription, where actions are relayed without modification; (2) transformation, where spatial mappings are adjusted to align disparate environments; and (3) translation, where actions are adapted to preserve sociocultural norms.

However, blended realities lacks a unifying language to compare how systems manage spatial differences. To address this gap, I present the Spatial Heterogeneity Framework, which characterises how systems support blended proxemics and where design interventions become necessary. Finally, through a qualitative study with 20 participants, I examine how people prioritise spatial accuracy and adhering to sociocultural norms.

This thesis makes three contributions: (1) the Spatial Heterogeneity Framework, which explains how increasing spatial dissimilarity reduces embodied actions afforded “for free” and raises the likelihood of perceptual distortions; (2) an extension of Expectancy Violations Theory to explain how people evaluate trade-offs between spatial accuracy and sociocultural expectations; and (3) an ethical analysis of adapting embodied actions, highlighting tensions between transparency and cognitive load.

Together, these contributions lay a theoretical foundation for context-aware blended realities.