  As an emerging interaction paradigm, physiological computing is increasingly
being used to both measure and feed back information about our internal
psychophysiological states. While most applications of physiological computing
are designed for individual use, recent research has explored how biofeedback
can be socially shared between multiple users to augment human-human
communication. Reflecting on the empirical progress in this area of study, this
paper presents a systematic review of 64 studies to characterize the
interaction contexts and effects of social biofeedback systems. Our findings
highlight the importance of physio-temporal and social contextual factors
surrounding physiological data sharing as well as how it can promote
social-emotional competences on three different levels: intrapersonal,
interpersonal, and task-focused. We also present the Social Biofeedback
Interactions framework to articulate the current physiological-social
interaction space. We use this to frame our discussion of the implications and
ethical considerations for future research and design of social biofeedback
interfaces.
