6 research outputs found
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Emotional Biosensing: Exploring Critical Alternatives
Emotional biosensing is rising in daily life: Data and categories claim to know how people feel and suggest what they should do about it, while CSCW explores new biosensing possibilities. Prevalent approaches to emotional biosensing are too limited, focusing on the individual, optimization, and normative categorization. Conceptual shifts can help explore alternatives: toward materiality, from representation toward performativity, inter-action to intra-action, shifting biopolitics, and shifting affect/desire. We contribute (1) synthesizing wide-ranging conceptual lenses, providing analysis connecting them to emotional biosensing design, (2) analyzing selected design exemplars to apply these lenses to design research, and (3) offering our own recommendations for designers and design researchers. In particular we suggest humility in knowledge claims with emotional biosensing, prioritizing care and affirmation over self- improvement, and exploring alternative desires. We call for critically questioning and generatively re- imagining the role of data in configuring sensing, feeling, ‘the good life,’ and everyday experience
Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI
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.Comment: [Accepted version, 32 pages] Clara Moge, Katherine Wang, and Youngjun
Cho. 2022. Shared User Interfaces of Physiological Data: Systematic Review of
Social Biofeedback Systems and Contexts in HCI. In CHI Conference on Human
Factors in Computing Systems (CHI'22), ACM,
https://doi.org/10.1145/3491102.351749