The present work explores the social dynamics of expressive biosignals: leveraging wearable technologies to introduce sensed physiological data as a means of clarifying the emotional or psychological processes underlying our subjective experiences. We developed an Android application that linked to a wearable heart rate sensor and allowed for the direct sharing and real-time broadcasting of users’ heart rate via text messaging. We deployed this application in a two-week field study to investigate the contextual triggers, perceptions, and consequences of users’ sharing behaviors. The study (N=13) utilized a combination of Experience Sampling Methodology (ESM) and qualitative interviews to discover the situations in which users were more or less likely to share their heart rate with contacts, and the subsequent interactions that occurred after sharing. The results revealed that participants used heart rate sharing as a means to express emotions and provide daily updates, as well as simply a novel and playful form of communication. They reported a variety of communicative consequences of their sharing as well as specific logistical and psychological barriers to sharing. The implications of these results for the design of expressive biosignal sharing systems for supporting positive social interactions are discussed.

We present Animo, a smartwatch app that enables people to share and view each other's biosignals. We designed and engineered Animo to explore new ground for smartwatch-based biosignals social computing systems: identifying opportunities where these systems can support lightweight and mood-centric interactions. In our work we develop, explore, and evaluate several innovative features designed for dyadic communication of heart rate. We discuss the results of a two-week study (N=34), including new communication patterns participants engaged in, and outline the design landscape for communicating with biosignals on smartwatches.

With the growing ubiquity of wearable devices, sensed physiological responses provide new means to connect with others. While recent research demonstrates the expressive potential for biosignals, the value of sharing these personal data remains unclear. To understand their role in communication, we created Significant Otter, an Apple Watch/iPhone app that enables romantic partners to share and respond to each other's biosignals in the form of animated otter avatars. In a one-month study with 20 couples, participants used Significant Otter with biosignals sensing OFF and ON. We found that while sensing OFF enabled couples to keep in touch, sensing ON enabled easier and more authentic communication that fostered social connection. However, the addition of biosignals introduced concerns about autonomy and agency over the messages they sent. We discuss design implications and future directions for communication systems that recommend messages based on biosignals. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; Empirical studies in collaborative and social computing; Empirical studies in ubiquitous and mobile computing.

We explore the potential for expressive biosignals, or displays of sensed physiological data as social cues, to influence perceptions of a member of a stigmatized group. In a between-subjects experiment (N=62) participants read a fictional interview with a drug addict in prison, and rated their empathy and closeness with the interviewee. Participants were randomly assigned to read either 1) the transcript of the interview by itself, 2) the transcript with a text description of the interviewee's heart rate, or 3) the transcript with a graph of the interviewee's heart rate. Results demonstrate that providing information about heart rate can increase empathy in terms of emotional perspective-taking. Additionally, visualizing the heart rate as a graph, as opposed to text, can increase closeness. We discuss the implications of these results and present suggestions for future directions. CCS Concepts: • Human-centered computing → Empirical studies in HCI; Empirical studies in collaborative and social computing.

We are exploring the concept of expressive biosignals: leveraging wearable technologies to introduce sensed physiological data as cues for social perception. Biosignals can help us achieve a deeper understanding of each other by revealing or clarifying the psychological processes that underlie our subjective experience. We conducted an exploratory study investigating expressive biosignals, comparing the influence of a variety of brain activity visualizations on impression formation. Results revealed that while participants readily infer emotional and cognitive states from visualized brain activity, the ambiguity of the data can lead to diverse perceptions and interpretations. Participants also expressed concerns that the observation of another individual's data during interaction might be invasive or distracting. We present a set of design considerations addressing issues of interpretability, integration, and privacy of biosignals in interpersonal contexts.