Understanding human experience through behavior.

IEEE · 12th ICVR · 2026

Recognizing disruption
through movement.

Can movement reveal when the relationship between a person and a system changes? This study analyzed head and controller motion during a coordination task, introducing unexpected changes in how objects responded.

Detrended fluctuation analysis identified differences between disrupted and uninterrupted phases within individual sessions. Detection depended on the thresholds selected, showing why context and calibration matter when interpreting behavioral signals.

For Response Reality, the broader direction is to turn ongoing interaction into useful information: recognize a change in coordination, then help a system decide when to clarify, adjust or offer support. The study establishes a basis for this direction in a controlled virtual task.

Computers in Human Behavior Reports · 2026

The avatar as a tool.

When does a virtual body become part of the interaction? Harris and colleagues varied the delay between a participant’s movement and an avatar’s response, comparing first-person and third-person perspectives.

Movement dynamics changed with delay in first-person avatars, while third-person patterns remained stable across delay levels. The findings highlight how perspective shapes the connection between embodiment and presence.

For human-aware systems, the design implication is that movement becomes meaningful through its relationship with the interface and the feedback it provides. This supports our focus on understanding the quality of the interaction as it unfolds.

PRESENCE: Virtual and Augmented Reality · 2025

Detecting changes
in interaction.

A controlled virtual task introduced disruptions to investigate changes in movement dynamics and breaks in presence.

The findings show how changes in human experience can be detected through movement dynamics during controlled VR interaction. This provides a foundation for studying the relationship between human behavior and technological feedback.

LMU University Hospital · Munich · 2025

Emergency and
medical simulation.

With LMU University Hospital in Munich, the team investigates movement-based measurement in emergency simulations, comparing it with physiological signals and self-report.

By examining interaction in XR and real-world scenarios, the project explores how behavioral measurement relates to immersion and task demands in a high-stakes training environment.

Project lead: Selina Kim.

CRISP · Crisis Simulation for Peace · 2025

AI-driven
interactive training.

Our work with CRISP contributes to immersive conflict-resolution training and meaningful human-AI interaction, informed by the needs of youth work professionals.

Virtual characters respond within challenging social situations. Designing these interactions connects our research on human experience with systems that adapt meaningfully to the person.