I think I don't feel sick: Exploring the Relationship Between Cognitive Demand and Cybersickness in Virtual Reality using fNIRS

Title of the Paper

I think I don’t feel sick: Exploring the Relationship Between Cognitive Demand and Cybersickness in Virtual Reality using fNIRS

Paper Information

• Research Domain: Human-Computer Interaction (HCI), Virtual Reality (VR), Cognitive Load, and Cybersickness Studies
• Keywords: Cybersickness, Virtual Reality, Cognitive Load, fNIRS, Head-Mounted Display, User Experience, Self-Perception, Workload, Neuroscience

Research Background and Problem Statement

• Identified Problems or Challenges:
  • Virtual reality users often experience cybersickness, primarily caused by mismatches between visual and vestibular perception.
  • Cybersickness reduces user immersion, enjoyment, and may hinder engagement and the effectiveness of applications such as learning and therapy.
  • Detection of cybersickness typically relies on self-reports from participants, which fail to capture the dynamic progression of symptoms and may influence users' perception of symptoms.
• Importance of the Research:
  • Understanding cybersickness and its mitigation methods can enhance user experience, adoption, and commercial success of VR applications.
  • Continuous monitoring of physiological signals (e.g., brain activity) offers a feasible method for real-time detection of cybersickness.
• Motivation and Related Work:
  • Current research primarily focuses on sensory input adjustments (e.g., field-of-view restrictions) to alleviate symptoms, but these interventions may reduce immersion.
  • High cognitive tasks have been shown to reduce motion sickness in real-world environments, but the relationship between visual motion and cognitive load in VR remains unclear.
  • fNIRS (functional near-infrared spectroscopy) has demonstrated potential in HCI for detecting cognitive load and emotional arousal, suggesting it could be a tool for monitoring cybersickness.

Solution

• Proposed Method or Solution:
  • Conduct experimental research to explore the potential alleviating effects of cognitive tasks on cybersickness.
  • Use fNIRS sensors to record prefrontal brain activity and preliminarily investigate the physiological signal correlations of cybersickness.
• Innovative Aspects:
  • First detailed quantitative analysis of the relationship between cognitive tasks and cybersickness.
  • Proposal to embed prefrontal fNIRS sensors in VR headsets to enable real-time evaluation of user experience.
• Implementation Steps and Key Techniques:
  • Experimental Design: Participants perform a rapid serial visual presentation (RSVP) task in a virtual roller coaster scenario under four experimental conditions (motion/stationary + task/no task).
  • Data Collection: Record Fast Motion Sickness Scale (FMS), NASA-TLX workload, SSQ post-test scores, and fNIRS brain activity signals.
  • Data Analysis: Use linear mixed-effects models to analyze the impact of cognitive load on cybersickness and response time, while examining fNIRS brain region activation changes.

Research Findings

• Specific Results:
  • User Experience: Experimental results indicate that performing cognitive tasks alleviates cybersickness, particularly during virtual roller coaster motion (supported by partial FMS data, but not reflected in SSQ data).
  • Brain Activity Detection:
    • fNIRS measurements show significant activation of the right dorsolateral prefrontal cortex (DLPFC), associated with cognitive tasks and cybersickness experience.
    • When both cognitive tasks and motion conditions are present, prefrontal activation decreases, possibly due to competition for cognitive resources.
• Advantages Compared to Existing Solutions:
  • Suggests that cognitive load may interfere with cybersickness, offering new insights for dynamically adjusting VR content design.
  • fNIRS-based data indicates that cybersickness could be detected through physiological signals, laying the foundation for scientific research and commercial development.
• Experimental and Evaluation Results:
  • RSVP task performance declines due to cybersickness, with longer response times, indicating complex interactions between cognitive load and perceived symptoms.
  • fNIRS signals exhibit significant changes under specific cognitive or cybersickness conditions, further validating its feasibility as a potential detection tool.
• Limitations and Future Directions:
  • Limitations:
    • Short experimental duration may restrict comprehensive symptom manifestation.
    • Inconsistent results between FMS and SSQ scales require further validation.
    • Simple experimental controls lack more complex or highly interactive simulation scenarios.
  • Future Directions:
    • Investigate the alleviating effects of cognitive tasks in longer exposure and more complex VR environments.
    • Develop a real-time cybersickness dashboard based on fNIRS to evaluate the relationship between perception and physiological variables.
    • Study how specific task types and designs influence cybersickness experiences across different user groups.