Understanding and Designing Avatar Biosignal Visualizations for Social Virtual Reality Entertainment

Title of the Paper

Understanding and Designing Avatar Biosignal Visualizations for Social Virtual Reality Entertainment

Paper Information

• Subject Area: Virtual Reality (VR), Human-Computer Interaction Design, Social Entertainment
• Keywords: Biosignals, Social Virtual Reality, Visualization, Entertainment, Virtual Reality, Perception, Design

Research Background and Issues

• Problems and Challenges:

  • Communication in VR social environments may be limited due to the lack of traditional nonverbal behavioral cues (e.g., facial expressions and gestures).
  • Biosignals (e.g., heart rate and breathing rate) can serve as tools to enhance social expression, but it remains unclear how to design effective biosignal visualizations in social VR entertainment scenarios and understand user perception.
  • Existing research has explored various forms of biosignal visualization, but challenges remain in designing visualizations that are both interpretable and non-intrusive.

• Significance:

  • Biosignals can improve social experiences, such as enhancing empathy, improving interaction quality, and increasing immersion.
  • Developing signal visualizations suitable for entertainment applications can enhance the realism and enjoyment of virtual spaces.

• Research Motivation:

  • To explore how users perceive virtual avatars and biosignals in VR social environments.
  • To propose design solutions suitable for social entertainment to optimize user experience.
  • To study user cognition and preferences regarding current visualization methods (e.g., colors, particle effects).

Solutions

• Methods and Approach:

  1. Mixed-Methods Research Framework: Combining questionnaires, context mapping, co-design, and user experiments.
  2. Two-Part Study:
     • Part 1: Explore how users perceive virtual avatars and biosignals, and generate initial concepts for biosignal visualization through co-design.
     • Part 2: Evaluate the impact of signal types (heart rate and breathing rate), rates (low/medium/high), and visual forms by comparing various visualization designs in a virtual jazz bar scenario.

• Innovations:

  • First to integrate biosignal visualization into VR social entertainment design, focusing on non-intrusiveness and interpretability.
  • Introduced multiple visualization designs (realistic, particle-based, virtual creatures, environmental changes) and validated them against user preferences.
  • Integrated user-avatar relationships, novel scenarios, and multidimensional signal characteristics into the design, proposing guidelines for dynamic social environments.

• Implementation Steps:

  1. Investigating User Needs and Preferences:
     • Conducted surveys (N=54) and context mapping (N=6) to analyze current user perceptions of biosignals and virtual avatars.
     • Categorized user engagement levels and social scenario characteristics (low/medium/high interaction).
  2. Co-Designing Biosignal Visualizations:
     • Conducted online co-design sessions (N=6) to conceptualize signal visualizations suitable for social VR entertainment and summarized design principles.
  3. Virtual Scene Experiment:
     • Built Unity VR scenes, implementing four visualization designs (realistic, particle-based, virtual creatures, environmental changes) and generating heart rate/breathing signals.
     • Conducted experiments in a jazz bar scenario (N=32) to measure user feedback on perceived arousal states, intrusiveness, and design preferences.

Research Findings

• Specific Findings:

  • Perceived Arousal States:
    • Realistic designs were most effective in distinguishing different rate states (low-medium-high).
    • Different visualization types showed varying effects on user perception depending on the signal type (heart rate vs. breathing).
  • Intrusiveness:
    • For heart rate signals, realistic and particle-based designs were the least intrusive to user experience.
    • For breathing signals, no significant differences in intrusiveness were observed across designs.
  • User Preferences:
    • Realistic designs were most preferred for heart rate signals (84.4%), while for breathing signals, they were equally favored alongside environmental visualization designs.

• Advantages Over Existing Solutions:

  • Provided design consensus tailored to specific scenarios (social entertainment) and multidimensional factors (signal type, rate, visual representation).
  • The proposed visualizations are not only interpretable but also consider peripheral attention needs, adapting to the dynamic nature of entertainment-focused social VR.

• Experiment and Evaluation Results:

  • Users rated the overall immersion of the virtual jazz bar scenario highly (IPQ "spatial presence" score: 5/7).
  • Users expressed cautious attitudes toward biosignal privacy issues but were open to blurred or abstract designs.

• Limitations and Future Directions:

  1. Simplified Biosignal Generation: The study used simulated signals rather than real-time biosensing data; future work could integrate actual physiological data to enhance ecological validity.
  2. Visual-Only Mode: The study focused on visual visualizations; future research should explore the application of auditory and haptic modalities.
  3. Expansion to New Scenarios: Test visualization adaptability in more types of social scenarios (e.g., virtual collaboration, education).
  4. Privacy Protection Mechanisms: Further address privacy concerns regarding signal sharing, such as through customization or encryption methods.