Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI

Title of the Paper

Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI

Paper Information

• Subject Area: Human-Computer Interaction and Social Biofeedback Systems
• Keywords: Physiological Computing, Social Biofeedback, Physiological Data Sharing, Computer-Mediated Communication, Emotional Communication, Systematic Review

Research Background and Issues

• Identified Problems or Challenges:

  1. Physiological computing technologies are increasingly used to measure and provide feedback on psycho-physiological states. However, most of these systems focus on single-user applications, with limited exploration of how biofeedback can enhance interpersonal communication in multi-user contexts.
  2. Although previous studies suggest that sharing physiological data can promote understanding of others' emotions and improve social skills, there is a lack of systematic understanding of this technology, particularly in terms of the physical, temporal, and social contexts of system interaction.
  3. There is insufficient research on how biofeedback systems can support users in practicing and developing social-emotional skills, such as empathy and emotion regulation.

• Significance of the Research:

  1. Using physiological signals as a medium of communication offers new technological possibilities for addressing social isolation and enhancing interpersonal relationships.
  2. A deeper understanding of the role of physiological data in different social contexts can guide future technology design to meet fundamental human needs for belonging and interaction.

• Motivation and Related Work:

  • Limitations of related work include the lack of comprehensive exploration of social contexts in biofeedback and insufficient quantification of its benefits for positive emotions or social skill development. This study aims to fill this academic gap.

Proposed Solution

• Proposed Solution:

  1. Conduct a systematic literature review to summarize the social interaction characteristics and impacts of biofeedback.
  2. Propose a new framework—Social Biofeedback Interactions Framework—to formally summarize interaction patterns in the field of social-physiological interaction.
  3. Perform qualitative analysis and meta-analysis to explore the effects of biofeedback on positive emotions and the development of social-emotional skills.

• Innovative Contributions:

  1. Treating the sharing of physiological signals as a novel communication medium, analyzing the impact of spatiotemporal scenarios and social relationships on interactions.
  2. Proposing a multidimensional framework to explore the fundamental structure of physiological social spaces in HCI from the perspectives of "symmetry" and "biofeedback access permissions."

• Implementation Steps:

  1. Literature search and screening: Following the PRISMA process, select 64 related articles from multiple databases.
  2. Data extraction and organization: Summarize and extract research contexts (physical and temporal characteristics), biofeedback features, and application domains.
  3. Qualitative and meta-analysis: Use thematic analysis to explore mechanisms affecting social-emotional abilities and conduct meta-analysis to assess the extent of their impact on positive emotions.

Research Outcomes

• Specific Findings:

  1. Categorized and summarized 64 studies on social biofeedback systems, covering the interaction characteristics between physical-temporal contexts and social relationships.
  2. Developed the "Social Biofeedback Interactions Framework" to describe the current interaction space of social biofeedback.
  3. Qualitative analysis identified six major themes (e.g., mindful self-awareness, empathy, social connection skills) and their corresponding social-emotional abilities.
  4. Meta-analysis indicated that social biofeedback systems have small to large effects on positive emotions.

• Advantages over Existing Solutions:

  1. Provides a more comprehensive understanding of biofeedback systems from the dimensions of physical, contextual, and social relationships.
  2. Emphasizes that social biofeedback not only temporarily enhances user experience but may also contribute to the long-term development of social-emotional skills.

• Experimental or Evaluation Results:

  1. Meta-analysis results showed that in six studies measuring positive emotions, the effect of biofeedback on positive emotions ranged from small to large (effect size d range: 0-1.46).
  2. Symmetric systems were found to better promote intimate relationships, while asymmetric systems were more suitable for public or group interactions.

• Limitations and Future Directions:

  1. Limitations:
     • Inevitably excluded some relevant cases during literature screening, such as specific unimodal biofeedback studies.
     • The meta-analysis lacked consistency due to diverse evaluation methods and had a relatively small number of studies.
  2. Future Directions:
     • Explore biofeedback designs that influence social norms and study their long-term effects on group relationships and privacy.
     • Conduct longitudinal studies on the dynamic impacts of social biofeedback systems in different usage scenarios.
     • Develop customized biofeedback system designs tailored to different social relationships and task purposes.