ZonAware: Identifying Zoning Out and Increasing Engagement in Upper Limb Virtual Reality Rehabilitation.

Abstract

Zoning out, a form of cognitive disengagement, seriously challenges the effectiveness of virtual reality (VR) based upper limb rehabilitation. As therapy often involves repetitive tasks requiring sustained attention, undetected lapses in focus can reduce motor learning, engagement, and overall recovery outcomes. This research addresses this gap by proposing ZonAware, a novel strategy integrating real-time zoning out detection with adaptive intervention to enhance user engagement during VR rehabilitation. ZonAware identifies zoning out using five eye-tracking metrics: blink frequency, blink duration, pupil size, eye openness, and gaze duration. These signals are analysed through lightweight statistical models (Z-Score, Boxplot, and Modified Z-Score), with a hard voting mechanism producing binary classifications in real-time. Upon detection, a pattern changing intervention subtly modulates task difficulty by temporarily increasing, then decreasing it, to regain user focus without breaking immersion. Three user studies involving 70 healthy participants and 22 patients demonstrated the strategy's effectiveness. ZonAware achieved 98.24% detection accuracy with low latency (82-150 ms), reducing zoning out frequency by 53.57% and shortening disengagement duration from 18.1 to 4.8 seconds. The approach also improved user engagement, performance, and emotional motivation. ZonAware delivers one of the first real-time zoning out solutions for VR rehabilitation, offering an interpretable, theory-driven approach that enhances attention, engagement, and adaptability in human-computer interaction.