Identification of Language-Induced Mental Load from Eye Behaviors in Virtual Reality

Area of Science:

• Human-Computer Interaction
• Cognitive Science
• Virtual Reality

Background:

• Intrusive methods for assessing user states can disrupt virtual reality (VR) experiences.
• Behavioral measures, particularly eye tracking, are increasingly used as non-intrusive alternatives.
• Current eye-tracking analyses in VR often focus on content-dependent metrics.

Purpose of the Study:

• To investigate the utility of content-independent eye metrics for identifying mental load in VR users.
• To explore pupil size, blink rate, and a novel metric, focus offset, as indicators of cognitive effort.
• To induce and measure mental load using auditory stimuli independent of visual content.

Main Methods:

• Participants experienced auditory stimuli (native and foreign languages) in a virtual phone booth within a VR environment.
• Eye-tracking data, including pupil size, blinks, and focus offset, were collected.
• Mental load was manipulated through auditory stimuli, and its correlation with eye metrics was analyzed.

Main Results:

• Increased mental load correlated with a significant increase in relative pupil size (0.512 SDs) and reduced variance.
• Mental load also led to fewer fixations and less voluntary gazing at distracting elements.
• A larger focus offset, indicating a 'staring into the distance' phenomenon, was observed with increased mental load.

Conclusions:

• Content-independent eye metrics, such as pupil size and focus offset, are viable indicators of mental load in VR.
• These findings support the use of non-intrusive eye-tracking measures for evaluating user cognitive states in VR.
• Further research and technological advancements are encouraged to enhance the stability and application of these metrics.