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As an emerging interaction paradigm, physiological computing is increasinglybeing used to both measure and feed back information about our internalpsychophysiological states. While most applications of physiological computingare designed for individual use, recent research has explored how biofeedbackcan be socially shared between multiple users to augment human-humancommunication. Reflecting on the empirical progress in this area of study, thispaper presents a systematic review of 64 studies to characterize theinteraction contexts and effects of social biofeedback systems. Our findingshighlight the importance of physio-temporal and social contextual factorssurrounding physiological data sharing as well as how it can promotesocial-emotional competences on three different levels: intrapersonal,interpersonal, and task-focused. We also present the Social BiofeedbackInteractions framework to articulate the current physiological-socialinteraction space. We use this to frame our discussion of the implications andethical considerations for future research and design of social biofeedbackinterfaces.

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