Mapping the Landscape of Affective Extended Reality: A Scoping Review of Biodata-Driven Systems for Understanding and Sharing Emotions

Paper Title

Mapping the Landscape of Affective Extended Reality: A Scoping Review of Biodata-Driven Systems for Understanding and Sharing Emotions

Publication Info

• Topic area: Affective computing in extended reality (XR) systems using biodata for emotion understanding and sharing.
• Keywords: Affective XR, biodata, emotion sharing, virtual reality, augmented reality, mixed reality, biofeedback, empathy, emotion regulation, human-computer interaction.

Background and Problem

• Problem / challenge: The field of XR systems leveraging biodata for emotion understanding and sharing is fragmented, with no systematic synthesis of design considerations, challenges, and opportunities.
• Significance: Understanding and sharing emotions in XR can enhance applications in healthcare, gaming, education, and collaboration, but the lack of a coherent framework limits effective design and implementation.
• Motivation and related work: Prior reviews have explored empathic computing and biodata systems but lack focus on biodata-driven XR systems. Existing studies often overlook XR-specific affordances and fail to address single-user and multi-user contexts comprehensively.

Solution

• Proposed approach: A scoping review of 82 papers to map the landscape of affective XR systems, focusing on biodata-driven emotion understanding and sharing.
• Novelty:
  1. Introduced the concept of "affective XR" to unify biodata-driven emotion-sharing systems.
  2. Developed a taxonomy of biodata flows in XR, including 10 sharing approaches.
  3. Identified nine design dimensions for emotion representation and four key challenges in affective XR.
  4. Highlighted underexplored design opportunities and future research directions.
• Procedure and key techniques:
  • Conducted a scoping review using a systematic search across four databases.
  • Screened 4,280 records, resulting in 82 relevant papers.
  • Categorized systems based on biodata types, XR technologies, application domains, and evaluation methods.
  • Developed taxonomies and design dimensions through thematic analysis and clustering.

Results

• Concrete findings:
  • Most systems used heart rate (35 instances) and EEG (35 instances) as biodata.
  • VR was the dominant XR technology (61 papers), followed by MR (11) and AR (7).
  • Four primary goals: emotion awareness (20 papers), regulation (30), social interaction (12), and adaptation (20).
  • Nine design dimensions identified, including literal vs. mapped visualizations, passive vs. proactive guidance, and real-time vs. retrospective data.
  • Four challenges: distrust in feedback, privacy concerns, cognitive overload, and interpretation difficulty.
• Advantage over baselines: The taxonomy and design dimensions provide a structured framework for analyzing and designing affective XR systems, addressing gaps in prior fragmented literature.
• Experiments / evaluation: Papers predominantly used self-report measures like SAM (15 papers) and PANAS (13), with limited exploration of multimodal feedback and AI-driven systems.
• Limitations and future work:
  • Limited exploration of AR/MR, passthrough AR, and augmented virtuality.
  • Underexplored design dimensions include interactive, deceptive, and collective representations.
  • Need for personalized and multimodal feedback, and ethical considerations for AI integration.

Summary

This scoping review introduces "affective XR" as a unifying concept for XR systems that use biodata to understand and share emotions. By analyzing 82 papers, the study develops taxonomies of biodata sharing and design dimensions for emotion representation, highlighting key challenges and underexplored areas. The findings reveal opportunities for advancing XR applications in healthcare, gaming, and collaboration through personalized, multimodal, and AI-driven designs. This work provides a foundation for future research to enhance emotion-sharing experiences in immersive environments.