Seeing Is Feeling: Emotional Cues in Others’ Heart Rate Visualizations

As more apps and interfaces use visualizations of other users’ biosignals to enhance non-verbal communication, we need to improve our understanding of how users interpret these cues. This study focuses on heart rate visualizations derived from electrocardiogram (ECG) signals. It contributes to the literature by summarizing prior insights on how users interpret two cues in particular: the level of heart rate and the extent of variations in heart rate. We conduct an online experiment with 66 participants based on actual ECG data. We investigate whether users associate certain cue combinations with specific emotions, whether we can observe differences in empathy-related measures, and whether users can form correct inferences on actions and events associated with heart rates. Our preliminary analysis indicates that one previously reported result is also observed in our study: elevated heart rate is associated with negative inferences about mood.